{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "480765be",
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.io import fits\n",
    "import HAWCtoHerschel as HtoH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d5477674",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Source information\n",
    "SourceName = 'Fil8'\n",
    "FullName = 'Filament 8'\n",
    "# Loading the fits files\n",
    "SourceT = fits.open('../FIELDMAPS_Plots/'+SourceName+'/Data/'+SourceName+'_Tdust_10_10.fits')\n",
    "SourceN = fits.open('../FIELDMAPS_Plots/'+SourceName+'/Data/'+SourceName+'_N_10_10.fits')\n",
    "SourcePol = fits.open('../FIELDMAPS_Plots/'+SourceName+'/Data/'+SourceName+'_Gal.fits')\n",
    "SourcePlanck = fits.open('../FIELDMAPS_Plots/'+SourceName+'/Data/'+SourceName+'_Planck.fits')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8fbf97a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot parameters\n",
    "ScaleLength = 0.0440737 # 0.0204628 # 1 pc in degrees for the target\n",
    "\n",
    "# Region location, width, and height\n",
    "l_center = 357.5414610 # Position in galactic longitude (degrees)\n",
    "b_center = -0.3558686 # Position in galactic latitude (degrees)\n",
    "l_width = 0.2903658 # Width in galactic longitude (degrees)\n",
    "b_height = 0.1718492 # Height in galactic latitude (degrees)\n",
    "Region = [l_center,b_center,l_width,b_height]\n",
    "\n",
    "# Intensity contours for the plot\n",
    "Icontours = [10, 20, 30, 40, 50, 60] # in mJy/arcsec^2\n",
    "# Ranges for plots\n",
    "Nscale = [0,2.0e+22] # Range for column density in cm^-2\n",
    "Tscale = [15.0,25.0] # Range for temperature map in K\n",
    "Iscale = [0.0,20.0] # Range for intensity map in mJy/arcsec^2\n",
    "# Vector scaling fraction in polarization plots\n",
    "Pvscale = 0.6\n",
    "\n",
    "# Figure size\n",
    "MapFigSize = [10.67,6] # in inches\n",
    "\n",
    "# Effective HAWC+ beam size to use\n",
    "HAWCBeam = 0.00519 # 18.7'' in Band E"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a2a163b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beam Size of polarization data\n",
      "18.2\n",
      "Beam size of target pojection\n",
      "36.395999999999994\n",
      "Pixel size of the polarization data\n",
      "4.550000000000001\n",
      "Pixel size of the target projection\n",
      "14.0000004\n",
      "Target standard deviation for smoothing in arcseconds\n",
      "13.384761981071023\n",
      "Target standard deviation for smoothing in pixels\n",
      "2.941705929905719\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: nan_treatment='interpolate', however, NaN values detected post convolution. A contiguous region of NaN values, larger than the kernel size, are present in the input array. Increase the kernel size to avoid this. [astropy.convolution.convolve]\n",
      "c:\\Users\\simon\\OneDrive\\Python\\FIELDMAPS_Testing_Herschel\\HAWCtoHerschel.py:96: RuntimeWarning: invalid value encountered in divide\n",
      "  dPI = ((StokesQ*dQ)**2.0 + (StokesU*dU)**2.0)**0.5/PI_biased\n",
      "c:\\Users\\simon\\OneDrive\\Python\\FIELDMAPS_Testing_Herschel\\HAWCtoHerschel.py:106: RuntimeWarning: invalid value encountered in divide\n",
      "  P_biased = 100.0*PI_biased/StokesI\n",
      "c:\\Users\\simon\\OneDrive\\Python\\FIELDMAPS_Testing_Herschel\\HAWCtoHerschel.py:109: RuntimeWarning: invalid value encountered in divide\n",
      "  dP = np.absolute(P_biased*((dPI/PI_biased)**2.0 + (dI/StokesI)**2.0)**0.5)\n",
      "c:\\Users\\simon\\OneDrive\\Python\\FIELDMAPS_Testing_Herschel\\HAWCtoHerschel.py:120: RuntimeWarning: invalid value encountered in divide\n",
      "  dO = (0.5*180.0/math.pi)*((StokesQ*dU)**2.0 +\n"
     ]
    }
   ],
   "source": [
    "# Reprojecting the HAWC+ Stokes data to the Herschel pixel scale\n",
    "NewPol = HtoH.ReprojectCube(SourcePol,SourceN, Smooth=True)\n",
    "#NewPol.writeto('test2.fits', overwrite=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "31eb9087",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\simon\\OneDrive\\Python\\FIELDMAPS_Testing_Herschel\\HAWCtoHerschel.py:228: RuntimeWarning: invalid value encountered in divide\n",
      "  imask_01 = np.where(Pdata[0].data/Pdata[1].data < IdI) # Total intensity SNR threshold\n"
     ]
    }
   ],
   "source": [
    "# Creating downsampled vector catalogs (independent vectors)\n",
    "# Creating the mask for the region\n",
    "DownsampleMask = HtoH.DownsampleVectors(NewPol,Step=2)\n",
    "# Creating the new catalogs for the region\n",
    "CatI, CatdI, CatQ, CatdQ, CatU, CatdU, CatP, CatdP, CatO, CatB,CatdO, CatPI, CatdPI, CatN, CatT = HtoH.MakePCats(SourceN, SourceT, SourcePol, NewPol, CatMask=DownsampleMask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2c4fb0cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "===\n",
      "Curve fit test\n",
      "Log scale fit: (-0.94811343279842,76.91369216831625)\n",
      "Direct power law fit: (-0.9650978225327917,86.07604916357634)\n",
      "===\n",
      "\n",
      "Power law index: -0.94811343279842 ± 0.04029269877510413\n",
      "Coefficient: 76.91369216831625 ± 8.24365717395673\n",
      "Chi-Squared: 272.527871294152\n",
      "Number of elements: 58\n",
      "Reduced Chi-Squared: 4.8665691302527145\n"
     ]
    },
    {
     "data": {
      "image/png": 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BgweVzp07K46OjkrdunWVw4cPK1999ZXSr18/S4emp02bNkpwcLDueVZWluLr66uEhITkuv/9+/cVGxsbZfPmzXrrW7Roofz3v//VPZ86darStGlTk2Lq3LmzEhoaatC+xsZv6DGFid8UhclXJaKm/rjsKfsqVqyot37NmjV4eHjQqFEjJk+ezP379/MsIy0tjaSkJL2lTCpfHho0AED1cBAaX19fxowZg6enpwUDE6JsOHDgAJ07d6Zv376cPHmS+vXrM336dGbPns20adP09p01axYuLi75LpGRkUUSZ3p6OkePHqV79+66dWq1mu7du7P/kSt9j8rMzCQrKwtHR0e99eXKlctRk7106RK+vr7UrFmTl19+2ezvw5T4jTmmqOPPzeM5LC0trcBjSlxS12g0jBs3jg4dOtCoUSPd+v/85z9899137Nixg8mTJ/Ptt9/yyiuv5FlOSEgI7u7uusXf3784wi+ZHl6CV+XxD1sIUXQmTJjA4MGDmTRpErVr1+all17it99+o2nTpjRv3lxv31GjRhEeHp7vUlRTIsfFxZGVlYWXl5feei8vL27dupXrMa6urrRr144ZM2YQHR1NVlYW3333Hfv37+fmzZu6/dq2bcuqVav4448/WLp0KREREXTq1Il79+7lKPPxHzZ79uxh1KhRBf6wMSV+Q48xJn5z8vf318tjISEhBR5T4ubVDA4O5vTp0zl+5b3++uu6x40bN8bHx4du3bpx5coVAgICcpQzefJkJkyYoHuelJRUdhN7+/awfLk2qb/1lqWjEaLMuH79Ovv37+ezzz7TrbO1tUVRlBy1dNBenXz8CqWx3n//fWbPnp3vPufOnTNbQ69vv/2WESNGUKVKFWxsbGjRogUvvfQSR48e1e3Tp08f3eMmTZrQtm1bqlWrxg8//EDQw6mhs40aNYoXXnhB9/zll19m4MCBPP/887p1RfXDJi/GxG9OUVFRelOvOjg4FHhMiUrqb731Fps3b2b37t34+fnlu2/bh1OLXr58Odek7uDgYNAHUCZ06KD9e+QIKgMu35iLRqMhKSkJNzc31OoSd1FIiCJ37tw5AFq0aKFbd+HCBdq0aUPjxo1z7D9r1ixmzZqVb5lnz56latWqeW5/5513GD58eL5l1KxZM8c6Dw8PbGxsiImJ0VsfExODt7d3nmUFBASwa9cuUlJSSEpKwsfHhyFDhuT6GtnKly9PnTp1uHz5co5tj/+wKVeuHJ6entTKnssiD6bEb+p7zi9+c3Jzcyud86krisJbb73Fzz//zF9//UWNGjUKPCY8PBwAHx+fIo7OCtSqBV5eqNLTsX/4uRUH6bsuyrrExERsbGxQqVQAxMfH89lnn+Hk5JTr/ua4/F65cmXq1auX72Jvb5/jOHt7e1q2bElYWJhunUajISwsjHbZXWPz4ezsjI+PD3fv3mXr1q30798/z32Tk5O5cuWKWb+/TYnf1PdcFPGbjdmb7Zlg9OjRiru7u7Jz507l5s2buuX+/fuKoijK5cuXlenTpytHjhxRIiIilF9++UWpWbOm8uSTTxr8GmW29Xu2QYMUBZT4d95RHjx4oFy+fFk5e/ZskbZ+N7UVu7R+F9bi0qVLCqBMnz5dOXfunNKzZ0+lRYsWipeXl3Lt2jVLh5fDunXrFAcHB2XVqlXK2bNnlddff10pX768cuvWLd0+ixYtUrp27ap7/scffyhbtmxRrl69qmzbtk1p2rSp0rZtWyU9PV23zzvvvKPs3LlTiYiIUPbu3at0795d8fDwUGJjY3PEcO/ePb08kNuSmZlpUvyPx27oezYmfnMoTL4qEUkdyHXJ7sYQGRmpPPnkk0rFihUVBwcHpVatWsqkSZOMesNlPqkvWKAooNx/8skSn9TT0tKUU6dOKWlpaSa8USFKlunTpyuVKlVSHB0dleHDhytxcXFKixYtlHr16lk6tFwtWrRIqVq1qmJvb6+0adNGOXDggN72qVOnKtWqVdM9X79+vVKzZk3F3t5e8fb2VoKDg5WEhAS9Y4YMGaL4+Pgo9vb2SpUqVZQhQ4Yoly9fzvX1p06dmmdOyF4iIiJMiv/x2A19z8bEbw6FyVcqRVGUYr44YBFJSUm4u7uTmJho9D0KqxAeDs2bo3FxIf3WLW7cukV6ejrx8fG0bNkSR0dHMjMzuX79Ot7e3ty6dQs/Pz9sbXM2u8je79Hthq4zRGpqKuHh4TRr1ixHVxkhhLB2hclXJeKeuigGjRujuLmhTk5GdfKk2YvXaDQkJyfL/XMhhLCgQiX1jIwMoqKiuHDhAvHx8eaKSRQFGxuUh/3V1UUwvGFhk7o0qhNCiMIzOqnfu3ePpUuX0rlzZ9zc3KhevTr169encuXKVKtWjddeey3HYP6iZFA6dgRAvXevhSPJKTupZ2ZmkpiYKMldCCFMYFRSnzt3LtWrVyc0NJTu3buzadMmwsPDuXjxIvv372fq1KlkZmbSs2dPevfuzaVLl4oqbmEC5WF/dfW+fVBCm1JoNBoSExMpI009hBDCrIwafObw4cPs3r2bhg0b5rq9TZs2jBgxgi+//JLQ0FD27NlD7dq1zRKoMIPWrVHs7VHdvo1dRATpfn4oikJCQoKMAy+EEFbAqJr6999/n2dCf5SDgwOjRo1ixIgRJgcmioCDA2nNmgHg+PAWiaIoJCUlyeVuIazE8ePHsbOzo0uXLkVSfvXq1XPMLa5SqQgODtbb78aNG7zyyitUqlSJcuXK0bhxY44cOZJnuYbMy24OWVlZfPjhh9SoUYNy5coREBDAjBkz8r06uHTpUpo0aaIb4a1du3Zs2bLF7LGZg1lav8fFxfHbb7/xv//9T28Qf1HypLZuDUC5XP6zREdHs2DBAqKjo4s7LCGEmYwZM4aJEydy4sSJIin/8OHDevOK//nnnwAMHjxYt8/du3fp0KEDdnZ2bNmyhbNnz/L5559ToUKFPMs1dF723Bgz5/rs2bNZunQpixcv5ty5c8yePZs5c+awaNGiPI/x8/Pj008/5ejRoxw5coSuXbvSv39/zpw5Y9BrFqdCJ/WffvqJWrVqMW3aNKZOnUpAQAChoaHmiE0Ugeyk7pjLL+YVK1Zw/vx5OX9ClFJr166lQoUKBAcHk5CQwLVr18z+GpUrV8bb21u3bN68mYCAADp37qzbZ/bs2fj7+xMaGkqbNm2oUaMGPXv2zHWeDoAHDx7w008/MWfOHJ588klq1arFxx9/TK1atVi6dKlZ49+3bx/9+/enb9++VK9enUGDBtGzZ08OHTqU5zH9+vXj6aefpnbt2tSpU4eZM2fi4uLCgYfTWZckRif15ORkvefTpk3j0KFDHDp0iOPHj7Nhwwb++9//mi1AYV5pLVui2Nhgd/06do/9Ag4KCqJevXoEBgYaVWZmZiZRUVFkZWWZM1QhhBFSUlL44IMPmD17Nn5+fri7u+vmyHicueZtT09P57vvvmPEiBG68e0B/ve//9GqVSsGDx6Mp6cnzZs3Z/ny5XmWY8y87IXVvn17wsLCuHjxIgAnTpzg77//1puJLT9ZWVmsW7eOlJQUg8bEL25GJ/WWLVvyyy+/6J7b2toSGxurex4TE5PrZAGiZFBcXFBatgTA6eBBvW2+vr6MHTvW6GkNMzMzuXnzptyXF8KCZs2aRe/evalfvz4ADRo0yDOpm2ve9k2bNpGQkJBjVrirV6+ydOlSateuzdatWxk9ejRjxoxh9erVuZZj6Lzsj75XU+ZcB+3UtC+++CL16tXDzs6O5s2bM27cOF5++eV83+upU6dwcXHRtRn7+eefadCgQYGfUXEzeurVrVu3EhwczKpVq1iyZAkLFixgyJAhZGVlkZmZiVqtNvjehrAMTZcuqA8dwunQIXjySUuHI4QopKtXr/LVV19x+vRp3bpGjRrlmdTNMW87aG/Z9enTJ8cPAI1GQ6tWrXTTyDZv3pzTp0/z5ZdfMmzYsFzLMmRe9myFmXP9hx9+YM2aNaxdu5aGDRsSHh7OuHHj8PX1zTM2gLp16xIeHk5iYiI//vgjw4YNY9euXSUusRud1KtXr85vv/3G999/T+fOnRkzZgyXL1/m8uXLZGVlUa9ePRmvu4TTdO4Mc+bgfOhQie2vLoQw3Pjx47lz5w5+fn66dRqNJs95180xb/s///zD9u3b2bhxY45tPj4+OZJd/fr1+emnn/Isz5h52U2dcx1g0qRJuto6QOPGjfnnn38ICQnJN6nb29vrym/ZsiWHDx9mwYIFfPXVVwW+ZnEyOqlne+mll+jTpw8TJ06kS5cuLFu2jGYPu0uJkk3zxBModnbY3bqF4/Xr4O1t6ZCEECbatm0be/fu5fjx43oTJx0+fJgRI0aQkJBA+fLl9Y55vKabm4Iuv4eGhuLp6Unfvn1zbOvQoQMXLlzQW3fx4kWqVatWwLvRzsvu7Oysm5d9zpw5BR5jjPv376NW6995trGxMfr2oUajIS0tzZyhmYVJSf3333/n3LlzNG3alK+//ppdu3bx8ssv06dPH6ZPn065cuXMHacwJycnUps1o9zhw5Q/fhylVStLRySEMEFGRgbjxo1j0qRJOSpV2bN7hYeH5+izXtjL7xqNhtDQUIYNG5brDIzjx4+nffv2zJo1ixdeeIFDhw6xbNkyli1bBsDixYv5+eefCQsL0x2zdetWFEWhbt26XL58mUmTJuXZcDc5OVmv0fa6desAuHXrlm5d5cqVsbGxyXFsv379mDlzJlWrVqVhw4YcP36cuXPn6o2r8nh8kydPpk+fPlStWpV79+6xdu1adu7cydatW4396Iqc0Q3l3nnnHQIDAzl8+DBvvPEGM2bMoHPnzhw7dgxHR0eaN29eYjvli389eOIJAMofO2bhSIQQplq8eDF37tzhrbfeyrHN398fJyenPO+rF8b27duJjIzMc4Cx1q1b8/PPP/P999/TqFEjZsyYwfz583WN0eLi4rhy5YreMYmJiQQHB1OvXj2GDh1Kx44d2bp1K3Z2djnK/+yzz/Dx8cl3iYqKyjW2RYsWMWjQIN58803q16/PxIkTdbks2+PxxcbGMnToUOrWrUu3bt04fPgwW7dupUePHkZ/dkXN6PnUK1WqxLZt22jZsiXx8fE88cQTuq4BoL0P88Ybb7Bnzx6zB1sYZX4+ddCbL/3Oxo1Uefll0itW5Nq+fdR82H/UlPnUU1NTOXToECqVitatW+vaVBgzn/qjsUVGRnL79m3dPO9CCFGWFOt86s7OzkRERAAQFRWV40u3QYMGJS6hi5xSmzVD4+CAfXw89o/9YhZCCFE6GZ3UQ0JCGDp0KL6+vnTu3FnvkoUoRRwceNC8OQBOJXBUJCGEEMYzuqHcyy+/TO/evbl69Sq1a9fO0apSlB4pbdvifOAA5R4bhEYIIUTpZFRNPXuEnkqVKtG6desCE7ohA/ELy7nfti2AdhAaGQ1OCCFKPaOSeuvWrXnjjTfynQ4vMTGR5cuX06hRo3wHGhCW96BhQ7LKlcMmIQFOnrR0OEIIIQrJqMvvZ8+eZebMmfTo0QNHR0datmyJr68vjo6O3L17l7Nnz3LmzBlatGjBnDlzePrpp4sqbmEOdnYkNmlCxYMHUe3ciSKDBwkhRKlmVE29UqVKzJ07l5s3b7J48WJq165NXFwcly5dArT3248ePcr+/fsloZcSCS1aAKDaudOygQghhCg0k0aUK1euHIMGDWLQoEHmjkcUs8SHLeBVe/ZAZmahy9NoNCQkJJTZsQCEEHmLiori1VdfJTY2FltbWz788EMGDx5s6bCsitFd2oR1Sa5dmyxXV1RJSWCG0eWyk7pMwyqEeJytrS3z58/n7NmzbNu2jXHjxpGSkmLpsKyKJPWyzsaGB23aAKD66y8LByOEsGY+Pj66Meq9vb3x8PAgPj7eskFZGUnqgpQOHQBQ//mnhSMRQpQVR48eJSsrC39//yJ7jU8//RSVSsW4cePy3CcrK4sPP/yQGjVqUK5cOQICApgxYwaPjqBevXp1VCpVjiU4OLjIYjeVyVOvitIvNjaW1atX83rPnngB7NuH6pGZj4QQoijEx8czdOhQli9fXmSvcfjwYb766iuaNGmS736zZ89m6dKlrF69moYNG3LkyBECAwNxd3dnzJgxurKysrJ0x5w+fZoePXqUyPYAJtXU//nnH3799VcOHTpk7nhEMdqwYQNXrlxh7b59KDVrosrMxFGGjBVCmGjw4MFUrlxZN8UqwMGDB7G3t2fbtm0ApKWlMWDAAN5//33at29fJHEkJyfz8ssvs3z5cipUqJDvvvv27aN///707duX6tWrM2jQIHr27KmX3ypXroy3t7du2bx5MwEBAXTu3LlI4i8Mo5P6999/T506dejfvz/t2rWjVatW3L59uyhiE0Vs8ODBBAQEMHjwYJSHUwiW273bwlEJIUqrhQsXMnDgQKZPnw5ok+srr7zC6NGj6dmzJ4qiMHz4cLp27cqrr76aZzmzZs3CxcUl3yV7hNPcBAcH07dvX7p3715gzO3btycsLEw32+iJEyf4+++/6dOnT677p6en89133zFixAhUKlWB5Rc3oy+/T5s2jf/85z9MnjyZqKgo3nvvPd5//31WrFhRFPGJIuTp6UlgYCBeXl7apP7VV5Tbs4esgg8VQogcfHx8GDduHF999RV37txh0qRJODg4MHv2bAD27t3L+vXradKkCZs2bQLg22+/pXHjxnrljBo1ihdeeCHf1/L19c11/bp16zh27Fi+I58+6v333ycpKYl69ephY2NDVlYWM2fO1M39/rhNmzaRkJDA8OHDDSq/uBmd1K9evcoff/xB9erVqVOnDt999x0tW7aUpF7KKU89hWJjg921a2iuXQOZx1wIYYI6derg5OTERx99xJo1azh06JBuiu6OHTsa1N21YsWKVKxY0ejXjoqKYuzYsfz55585pgXPyw8//MCaNWtYu3YtDRs2JDw8nHHjxuHr68uwYcNy7L9ixQr69OmT548KSzP68ntmZiZOTk665/Xq1UOj0XDr1i2zBiaKmZsbPPEEAOrt2y0WhkajITk5Wfq5C1FKqdVqGjduzBdffMEnn3xC06ZNjS7D1MvvR48eJTY2lhYtWmBra4utrS27du1i4cKF2Nra6jV2yzZp0iTef/99XnzxRRo3bsyrr77K+PHjCQkJybHvP//8w/bt2xk5cqTR76m4mNT6ffXq1XTo0IEmTZrg4uKCra0t9+/fN3dsophpevbEZu9ebde2Z56xTAwaDSkpKXrdSYQQpUf2/90WLVrwzjvv5LlfVlYWNjY2uW4z9fJ7t27dOHXqlN66wMBA6tWrx3vvvZfr692/fx+1Wr9+a2Njk2vFIjQ0FE9PT/r27ZtvbJZkdFLv1KkTn3zyCffu3UOtVlOjRg1SU1NZsWIF3bt3p1WrVri6uhZFrKKIKd27w9SpqHfuNMuQsUKIsmf+/PkcPHiQZs2a5UiWzz77LH5+fhw+fJg33ngjzxqvqZffXV1dadSokd46Z2dnKlWqpFu/ePFifv75Z8LCwgDo168fM2fOpGrVqjRs2JDjx48zd+5cRowYoVeORqMhNDSUYcOGYWtbcnuDGx3Zrl27ALh06RJHjx7l2LFjHDt2jKVLlxISEoJaraZ27dqcO3fO7MGKItayJVnly2OTkIBDeDhUr27piIQQpcipU6eYPHkyb775Jl9//TWZmZl6CfDUqVN069aNL774wmIxxsXFceXKFd3zRYsW8eGHH/Lmm28SGxuLr68vb7zxBh999JHecdu3bycyMjJHsi9pVIoZr3NGRERw5MgRjh8/zqxZs8xVrFkkJSXh7u5OYmJimZ1sJDMzk+vXr+Pt7c2NGzdIT08nLi4OLy8vatasCUDagAE4//YbCWPG4PL557n+Is0ux8/PD1tbW1JTUzl06BAqlYrmzZsTFxeHn58fgN5+hsTm4eHBn3/+ya+//sqUKVN0cQkhSrbU1FRat25NixYtmD9/PhUrVuTUqVO6GvK9e/do2LBhvl3RhFZh8pVZh4mtUaMGgwcPLnEJXRjuwZNPAubtr27sJC+//vorV65cITQ01GwxCCGK1vvvv09KSgqLFy+mQoUKVKtWjfnz5xMdHQ3AmTNnimywGfGvEjH2e0hICK1bt8bV1RVPT08GDBjAhQsX9PZJTU0lODiYSpUq4eLiwsCBA4mJibFQxNbrQadOANifPAl5TLQQHR3NggULdP9ZC2JsUu/Xrx8BAQEEBgYaFrQQwqK2bdvGkiVL+O6773RtqqZMmcKmTZt046OfOnUqR390YX4lIqnv2rWL4OBgDhw4wJ9//klGRgY9e/bUm5Jv/Pjx/Prrr2zYsIFdu3YRHR3N888/b8GorVOWjw+a+vVRaTR5ztq2YsUKzp8/X+DYBMYm/2weHh4MHz68xPYDFULo69mzJxkZGXo18ZEjRxIXF8fPP/8MSFIvLiWiCd8ff/yh93zVqlV4enpy9OhRnnzySRITE1mxYgVr166la9eugLZrQf369Tlw4ABPPOxfLQwXExPD2rVr6datG15eXnrbND16oD53DtWWLfDiizmODQoKIikpiaCgIN26uLg4Nm/ejLe3N3Z2dsC/yT80NFRvXyFE2bNw4UJLh1AmlIia+uMSExMBdF0ajh49SkZGht44vvXq1aNq1ars378/1zLS0tJISkrSW8S/1q9fz8WLF/n1119zbNM8HPNYtWUL5HLJ3NfXl7Fjx+rVpDdv3syVK1dYtWqVbl1QUBD16tUz+jJ6XFwcq1atMrqGL4QQ1uTxHJaWllbgMYWqqYeFhREWFkZsbGyO+6UrV640qUyNRsO4cePo0KGDrtXkrVu3sLe3p3z58nr7enl55TmSXUhICNOmTTMphrJgyJAhupr64zTt26NxdUV9+zYcPgxt2xZYXvv27Tl+/LjeJAjZyd/b29uoEQcfbSg3Y8YMg48TQghr8vhc81OnTuXjjz/O9xiTa+rTpk2jZ8+ehIWFERcXx927d/UWUwUHB3P69GnWrVtnchkAkydPJjExUbdERUUVqjxr4+XlRXBwMB4eHjk32tvzoGNH7ePffjOovH379uHm5saWLVsKHZs0lBNCCO1Y9o/mscmTJxd4jMk19S+//JJVq1blO32esd566y02b97M7t27df2cAby9vUlPTychIUGvth4TE4O3t3euZTk4OODg4GC22Mqa+9264bxlC2zeDA+nUczPM888w+bNm80yc1FBDeU0Gg1JSUm4ubnlGLFKCCGshZubW/H1U09PTzdbn0NFUXjrrbf4+eef+euvv6hRo4be9pYtW2JnZ6cb1g/gwoULREZG0q5dO7PEIPQ96NwZRaWC48fhxo0C9/fw8CAwMBAfH5989zO2e1tRlSGEENbI5KQ+cuRI1q5da5YggoOD+e6771i7di2urq7cunWLW7du8eDBAwDc3d0JCgpiwoQJ7Nixg6NHjxIYGEi7du2k5XsR0Xh4QOvW2ie//26+ciUhCyFEkTH58ntqairLli1j+/btNGnSRNeNKdvcuXMNLmvp0qUAdOnSRW99aGio7nLuvHnzUKvVDBw4kLS0NHr16mXR8YNLI7VaTfny5Q2+ZK15+mlsDh3S3ld/7bUijk4IIURhmZzUT548SbNmzQA4ffq03jaVSmVUWYYMP+/o6MiSJUtYsmSJUWWLf2Un9UwDZ2BTnn4aPv4Y/vwTUlPB0bFoAxRCCFEoJif1HTt2mDMOURI1awa+vhAdDbt2Qa9elo5ICCFEPqTpsMibSgV9+2ofb95s2ViEEEIUqFCDzyQkJLBixQrd3OkNGjQgKCgId3d3swQnSoBnnoHly7X31Rcu1CZ6IYQQJZLJNfUjR44QEBDAvHnziI+PJz4+nnnz5hEQEMCxY8fMGaOwpG7dwMEBIiLg7Nkie5nsyV/Cw8MJDQ0lLi6uyF5LCCGslclJffz48Tz77LNcu3aNjRs3snHjRiIiInjmmWcYN26cGUMUFuXsrE3sAJs2GXSIKd3Wsid/+eCDD7hy5Qqb5XK/EEIYrVA19ffeew9b23+v4Nva2vLuu+9y5MgRswQnSojnntP+NTCpK4pCYmKiUUk9e/KXWbNmERAQwDPPPGNCoEIIUbaZnNTd3NyIjIzMsT4qKgpXV9dCBSVKmH79tPfSjxyBIhpDP3vyl2bNmhEYGJj7mPRCCCHyZXJSHzJkCEFBQaxfv56oqCiioqJYt24dI0eO5KWXXjJnjMLSvLygQwftYwNr60IIIYqfya3fP/vsM1QqFUOHDtUNZmJnZ8fo0aP59NNPzRagKCGeew7+/lub1EePtnQ0QgghcmFyTd3e3p4FCxZw9+5dwsPDCQ8P17WAl9nRrNCAAdq/u3bBnTsWDUUIIUTuCj34jJOTE40bN6Zx48Y4OTmZIyZREtWsCU2aQFYWqsfmWI+OjmbVqlXSDU0IISzMqMvvEyZMYMaMGTg7OzNhwoR89zVmQhdhGSqVCmdn5xxj9ec58ctzz8HJk6j+9z/o2lW3OjQ0lCtXrvDrr7/So0eP4ghdCCFELoxK6sePHycjI0P3OC/GTugiLEOtVpOSksLq1at555138PX11a0vX758zgMGDIBp01Bt24bq4bS4AIGBgdy4cYN+/foZ9LrZ/dgrVqxo8IxxQgghCmZUUn90EpfVq1fj5+eX40tZURSiiqjbkzC/DRs2cPHiRVasWMGHH36Y/85Nm0L16qiuXaPc7t1Quzag7Y42fPhwg3/MZfdjN2YaWCGEEAUz+Ru1Ro0aud5DjY+Pp0aNGoUKShSfwYMHU7duXYKCggreWaXSDUTjtHVrEUcmhBDCWCYn9bzmQE9OTsZR5t0uNby8vBgzZozu0nuBnn8eAKft2yEtrQgjE0IIYSyj+6lnN5BTqVR89NFHei3es7KyOHjwIM2aNTNbgKKEad8exdcXdXQ0yvbt0L+/rvW7offU85J9rz2vH4xCCCHyZ3RN/fjx4xw/fhxFUTh16pTu+fHjxzl//jxNmzZl1apVRRCqKBHUapSHtXXVhg2Afuv3mzdvsnDhQmJiYowuWlEU7t27J0ldCCFMZHRNPbuxXGBgIAsWLMDNzc3sQQnLyLMr22M0gwahXrwY1a+/QlqaXuv3VatWceHCBdavX0+LFi2KKXIhhBBQiGFiQ0NDzRmHKAHy7Mr2uHbtyPT2xvbWLdi2Dd8ePXSt34cPH05ycjJDhgwp8niFEELoM7mhXEhICCtXrsyxfuXKlcyePbtQQYkSTq3mfp8+2sc//KC3ycfHhzFjxuDl5WWBwIQQomwzOal/9dVX1KtXL8f6hg0b8uWXXxYqKFHypfTtq33wyy+QmmrZYIQQQgCFSOq3bt3Cx8cnx/rKlStz8+bNQgUlSr605s1RqlSBe/dQb99u6XCEEEJQiKTu7+/P3r17c6zfu3ev4X2ehUWo1Wrc3d0LN5yvWo0ycCAANj/9ZKbIhBBCFIbJSf21115j3LhxhIaG8s8///DPP/+wcuVKxo8fz2uvvWbOGIWZGdrKvSCaQYO05W3ejFoGohFCCIszufX7pEmTuHPnDm+++Sbp6ekoikK5cuV47733eP/9980Zoyip2raFqlVRRUZScd8+7jwyc5upYmNjzTKQjRBClEUmV9VUKhWzZ8/m9u3bHDhwgJMnTxIfH89HH30ks7SVFWo1vPwyAJ5//mmWIjds2MDVq1fZvHlznvtER0ezYMECoqOjzfKaQghhLQo9RVZkZCR37tzh6tWrbN26lf/973/873//M0dsojR4mNQrHjyIbVJSoYsbPHgwNWvW5JlnnslznxUrVnD+/HlWrFhR6NcTQghrYvLl96tXr/Lcc89x6tQpVCqVbmjP7Fp6VlaWeSIUJVvDhmiaNkV94gQeO3ZA586FKs7T07PAaVyDgoJISkoybGY5IYQoQ0yuqY8dO5YaNWoQGxuLk5MTp0+fZvfu3bRq1YqdO3eaMURR0mU9HD3OXJfgC+Lr68vYsWOll4UQQjzG5KS+f/9+pk+fjoeHB2q1GhsbGzp27EhISAhjxowxZ4yihMt64QUUlQr3kydR/fOPpcMRQogyy+SknpWVhaurKwAeHh66RkvVqlXjwoUL5olOlA5VqpDQvDkAto8NGwvSsE0IIYqLyUm9UaNGnDhxAoC2bdsyZ84c9u7dy/Tp06lZs6bZAhSlQ2z37sDDpP7Y1KmhoaHSsE0IIYqByUl9ypQpaDQaAKZPn05ERASdOnXi999/Z+HChWYLUJQOcZ07o7G3x+b8eezPndPbFhgYSL169QgKCiI6Otrk+daFEELkz+Sk3qtXL55//nkAatWqxfnz54mLiyM2NpauZhiERJQuWS4u3GnfHgDXX37R2/Zow7YVK1bo5lsXQghhXiYl9YyMDLp168alS5f01lesWFEGninDYnv0AMBl82bIo0tjUFAQdevWlfnWhRCiCJjUT93Ozo6TJ0+aOxZRyt194gmUChWwjYmh3L59qKtXzzHGvK+vr/SOEEKIImLy5fdXXnlFGj4JHZVKhVP58mQ+rIG7/vij2SaOEUIIYRiTv20zMzNZunQprVq14o033mDChAl6izF2795Nv3798PX1RaVSsWnTJr3t2SOMPbr07t3b1NBFEVCr1bi4uKAZNgwAl23bID7epLJUKhUuLi7yY0AIIYxk8jCxp0+fpkWLFgBcvHhRb5ux99VTUlJo2rQpI0aM0DW+e1zv3r0JDQ3VPXdwcDAyYlEclGbNSKtfH4dz51CtXQvjxhldhlqtxtfXF1tbk/95CiFEmWTyt+aOHTvMFkSfPn3o06dPvvs4ODjg7e1tttcURSdp8GAqT5+OetUqk5K6SqWSy/ZCCGECo781r169qpu8pTjt3LkTT09P6taty+jRo7lz506++6elpZGUlKS3iOJxpV07PlaruXniBBw/bulwhBCiVHo8h6WlpRV4jNFJvXbt2ty+fVv3fMiQIUU+kEjv3r355ptvCAsLY/bs2ezatYs+ffrkOxNcSEgI7u7uusXf379IYxT/+n7LFo57erIcYOVKS4cjhBClkr+/v14eCwkJKfAYo5P647X033//nZSUFGOLMcqLL77Is88+S+PGjRkwYACbN2/m8OHD+c4GN3nyZBITE3VLVFRUkcYo/jVkyBBqt23LawBr1kBqqqVDEkKIUicqKkovj02ePLnAY0rlTcuaNWvi4eHB5cuX89zHwcEBNzc3vUUUDy8vL0bPmYOPvz/cvYvqsRHmhBBCFOzxHGZIA3Gjk3p2l7LH1xWn69evc+fOHXx8fIr1dYURbGxQhg4FQPVIrwUhhBBFx+jW74qiMHz4cN0vhtTUVEaNGoWzs7Pefhs3bjS4zOTkZL1ad0REBOHh4VSsWJGKFSsybdo0Bg4ciLe3N1euXOHdd9+lVq1a9OrVy9jwxSNUKhVubm7cv3/fLGW5u7vrtVjXDBuGeuZMVH/9hW1kJPj5Ffp1hBBC5M3omvqwYcPw9PTU3bh/5ZVX8PX11buZ7+7ublSZR44coXnz5jR/OCf3hAkTaN68OR999BE2NjacPHmSZ599ljp16hAUFETLli3Zs2eP9FUvJHOO+KZWq3MkdWrUgF69UCkKrmvX6lbHxMSwcOFCmV9dCCHMzOiaemgRXErt0qVLvt3ktm7davbXFMVk1CjYuhWXDRtQPv8cHBxYv349Fy5cYMWKFUybNs3SEQohhNUolQ3lhGUZVcN/5hkUPz9s4uNR/fQToG0dX7duXYKCgoo4UiGEKFskqQujGZXUbW3RPEze6q++ArSt48eMGYOvr2+uhyiKQkJCAhqNxmwxCyFEWSBJXRQ5ZcQIFBsbVPv2walTBe+vKCQlJUlSF0III0lSF0XP15f7PXoAoF62zMLBCCGE9ZKkLorFvZdfBkC1Zg2qIh6BUAghyqpCzW0ZFhZGWFgYsbGxOS6VrpQxv8UjUtu3R6ldG9WlS7j+8gtJ//mPpUMSQgirY3JNfdq0afTs2ZOwsDDi4uK4e/eu3iKEHrUazeuvA+C+ejXk0YVRpVLh7Oxc7KMUCiGENTC5pv7ll1+yatUqXn31VXPGI6yYEhiIMm0a9leuUO7vv6F6db3tMTExrFu3jsGDBxs9gJEQQohC1NTT09Np3769OWMRxcico8kZzN0dZfhw7cNVq3LE88svv3DhwgU2bNhQfDEJIYQVMfkbfeTIkax9ZOhPUbpYJKkDmuBgFJUK51274Px5vXiCg4OpV68egwcP/nd/jUb6rAshhIFMvvyemprKsmXL2L59O02aNMHOzk5v+9y5cwsdnLBCtWpxv2tXnMPCUC9aBA8HpAHw9fVlzJgxZGVl6dZlJ3UXFxfdDxBL/SARQoiSzuSkfvLkSZo1awbA6dOn9bZJIyeRn4TAQJzDwlB9+y2EhEDFikYdn53UhRBC6DM5qe/YscOccQgrkT1bW1JSUp77pLZtS1r9+jicOwfLl8N77xVjhEIIYb3k+qUoNLVarbs8btClcZWKxIcN5li8GDIyiiVOIYSwdoUafCYhIYEVK1Zw7tw5ABo0aEBQUJB0RypjHk3qhkp+5hkqf/45quvXYeNGGDKkCCMUQoiyweSa+pEjRwgICGDevHnEx8cTHx/PvHnzCAgI4NixY+aMUVghxcEBzahR2if/9395DkYjhBDCcCYn9fHjx/Pss89y7do1Nm7cyMaNG4mIiOCZZ55h3LhxZgxRWCtl1CgoVw6OHoWwMEuHI4QQpV6haurvvfcetrb/XsG3tbXl3Xff5ciRI2YJTli5ypVh5Ejt408/tWwsQghhBUxO6m5ubkRGRuZYHxUVhaura6GCEmXIO++Ara22pn74sKWjEUKIUs3kpD5kyBCCgoJYv349UVFRREVFsW7dOkaOHMlLL71kzhiFNatWDR7O2Kb+v/9DpVLh7u4uYx0IIYQJTG79/tlnn6FSqRg6dCiZmZkA2NnZMXr0aD6VS6nCGO++C998g2rTJhyCg3Hv0IEHDx5YOiodjUZDUlISbm5uMoqdEKJEM/kbyt7engULFnD37l3Cw8MJDw/XtYB3cHAwZ4yiCJWIIVcbNoT+/VEpCm6PDBtbUsj480KI0qLQ3+ROTk40btyYxo0b4+TkZI6YRDEq7qSePeJcjsvr778PgMumTRAVVSyxCCGEtTHq8vuECROYMWMGzs7OTJgwId99ZUIXkZvsHxHJycn6G554Ak3nzqh37cJ23jztJXkhhBBGMSqpHz9+nIyHQ3oeP348z/2kkZMwhfLBB7BrFzYrV2IzdCj4+Vk6JCGEKFWMSuqPTuKyevVq/Pz8cly2VRSFKLl8WqaY4xK+RqPhbvPmOLdqRbkjR3D/8kv4+mszRimEENbP5G/hGjVqEBcXl2N9fHw8NWrUKFRQonQxV1JPTEri7tixALh+/z3cuGGuEIUQokww+VtYyWOs7uTkZBwdHU0OSFgfY5L+gyeeQNOhA6r0dNSzZxdDdEIIYT2M7qee3UBOpVLx0Ucf6bV4z8rK4uDBgzRr1sxsAYrSLzupG0SlIvPDD7Hv3RvVihXSYE4IIYxgdFLPbiCnKAqnTp3C3t5et83e3p6mTZsyceJE80UoyhxN586ktm2L48GD2tr6e+9ZOiQhhCgVjE7q2Y3lAgMDWbBgAW5ubmYPSoiEcePwfuklVCtXYvPyy9ISXgghDGDyMLGhoaEAnD17lsjISNLT0/W2P/vss4WLTJRa5mg4l/rEE2ieegr1jh1UmD8f1q0zX4BCCGGlTE7qERERDBgwgFOnTqFSqXQN57L7qGdlZZknQlHqGHUPPR+amTNRt2+P88aNZJ06Bc2bFz44IYSwYiZXpcaMGUONGjWIjY3FycmJM2fOsHv3blq1asXOnTvNGKIoa6Kjo1mwYAHRVaqgGTQIlaKgnjLF0mEJIUSJZ3JS379/P9OnT8fDwwO1Wo1araZjx46EhIQwZswYc8YoypjQ0FDOnz/PihUruP7WW3ysUnHr999h925LhyaEECWayUk9KysLV1dXADw8PIiOjgagWrVqXLhwwTzRCatU0D33wMBA6tWrR1BQECv++otjfn4sB20r+DzGRxBCCFGIpN6oUSNOnDgBQNu2bZkzZw579+5l+vTp1KxZ02wBCutTUFL39fVl7Nix+Pr6EhQURK3evRnp6AgHDsCmTcUbrBBClCImJ/UpU6bo5peePn06ERERdOrUid9//52FCxeaLUBRtvn6+jLmgw/wGT9eu+KDDyAz07JBCSFECWVyUu/VqxfPP/88ALVq1eL8+fPExcURGxtL165djSpr9+7d9OvXD19fX1QqFZseq40pisJHH32Ej48P5cqVo3v37ly6dMnU0EUppHnnHahUCc6fh6++KtbX1jXce3iLSQghSirTOxLnomLFiiZNu5qSkkLTpk1ZsmRJrtvnzJnDwoUL+fLLLzl48CDOzs706tWL1NTUwoYsSgiNRkNycrLu6k8O7u4wY4b28UcfQXx8scW2YsUKXcM9IYQoyUxO6l27dmXatGk51t+9e9fomnqfPn345JNPeO6553JsUxSF+fPnM2XKFPr370+TJk345ptviI6OzlGjF6VXdlLPa6IgAF57DRo10ib0jz8uttiCgoJ0DfeEEKIkMzmp79y5k8WLFzNgwABSUlJ069PT09m1a5dZggPtIDe3bt2ie/fuunXu7u60bduW/fv353lcWloaSUlJeoso5WxtYf587eMvvoAzZ4rlZR9tuCeEEMXl8RyWlpZW4DGFuvy+fft2bt26xRNPPMG1a9cKU1Sebt26BYCXl5feei8vL9223ISEhODu7q5b/P39iyQ+Ucy6dYMBAyArC8aPly5uQgir5e/vr5fHQkJCCjymUEndx8eHXbt20bhxY1q3bl2iRpKbPHkyiYmJuiUqKsrSIQlz+ewzsLeHP/+EzZstHY0QQhSJqKgovTw2efLkAo8xOalnN4hzcHBg7dq1jB07lt69e/PFF1+YWmSuvL29AYiJidFbHxMTo9uWGwcHB9zc3PQWYSUCArS1dND+lQaTQggr9HgOc3BwKPAYk5P64w2apkyZwpo1a/j8889NLTJXNWrUwNvbm7CwMN26pKQkDh48SLt27cz6WqIU+e9/wdcXrlyBTz+1dDRCCFEiFGqWNg8PD711AwcOpG7duhw9etSospKTk7l8+bJe2eHh4VSsWJGqVasybtw4PvnkE2rXrk2NGjX48MMP8fX1ZcCAAaaGL0o7V1dYsAAGD4aQEPjPf6BOHUtHJYQQFmVyUq9WrVqu6xs1akSjRo2MKuvIkSM89dRTuucTJkwAYNiwYaxatYp3332XlJQUXn/9dRISEujYsSN//PEHjo6OpoYvrMHAgdCnD2zZAm++qb3HbsI4CUIIYS1USr4dg/VNmDCBGTNm4OzsrEu8eZk7d26hgzOnpKQk3N3dSUxMlPvrJVBqairHjh2jRo0a2NjYkJycTNWqVQG4fv06fn5+2Nrm8hv06lVo2FB7X33NGm2N3cwyMzPzj0EIIcyoMPnKqG+o48ePk5GRoXucF1NGlRNCrVbj6uqao1FkvmrWhA8/1N5jHz9eW3OvUKHoghRCiBLMqKS+Y8cOADIyMlCr1Xz55ZfUrl27SAITZUt0dDQrVqzg3XffzXP2tjxNnAjffQfnzmknfFm6tGiCFEKIEs6k1u92dnacPHnS3LGIMiw0NJTLly+zatUq4w+2t/83kX/5JZhhREONRkNCQkLeY9ELIUQJZHKXtldeeUUmuBBmExgYSK1atRg+fLhpBXTurB0bHiAoCO7fL1Q8hUnq8oNACGEpJrf6yczMZOXKlWzfvp2WLVvi7Oyst72kNZQTJZuvry9BQUH4+PgYd0/9Uf/3f9qW8FeuaO+xz5tn3iANlJ3UXVxcjL+VIIQQhWByUj99+jQtWrQA4OLFi3rbpKGcsAh3d1i+XNtYbsECGDQIOnSwdFRCCFFsTE7q2Y3mhLAEjUZDUlISbm5u+rXh3r0hMBBCQ2HECAgPh3LlLBanEEIUJ7k2KEqlfO9bz52rHUL24kWYMqX4gxNCCAsp9EgaZ8+eJTIykvT0dL31zz77bGGLFsI05cvDsmXwzDPaBP/009opW4UQwsqZnNSvXr3Kc889x6lTp1CpVLoJXrLvp2dlZZknQiFM0bcvvPEGfPUVDBsGJ05ApUomFaVWqylfvrw0ehNClHgmf0uNHTuWGjVqEBsbi5OTE2fOnGH37t20atWqRM2rLsqwzz+HunXhxg1tgjd8RGQ9ktSFEKWFyd9S+/fvZ/r06Xh4eKBWq1Gr1XTs2JGQkBDGjBljzhiFMI2zs3Y8eFtb+OknMGVgGyGEKEVMTupZWVm4uroC4OHhQXR0NKCdve3ChQvmiU6UeYWuJbdsCZ98on389tvwyBS/QghhbUxO6o0aNeLEiRMAtG3bljlz5rB3716mT59OzZo1zRagKNvMcul74kTtiHMpKfDii9oZ3YQQwgqZ/E05ZcoUXXei6dOnExERQadOnfj9999ZuHCh2QIUZUP2hC43b940f+E2NvDtt9qGckePwjvvGHW4scO+RkdHs2DBAt3VKyGEKC4mJ/VevXrx/PPPA1CrVi3Onz9PXFwcsbGxdO3a1WwBirKhUBO6GMLfX5vYAb74AtatM/hQY5P6ihUrOH/+vMyNIIQodmZtzluxYkUZIlaYpNATuhiiTx/tmPAAI0fC+fOA+SdgCQoKol69egQFBZmlPCGEMJRR/dQnTJhg8L4yoYswhlkmdDHEtGmwbx/s2KEdG/7QITT29madgMXX15exY8fi6+trhoCFEMJwRiX148ePG7Sf1NZFYahUqpxjupuLjQ2sXQvNm8OZMzBqFMhlciGElTAqqcskLqKo3bx5ky+++ILx48fj4eFRNC/i7a29p96tG3z7LaomTbS1diGEKOUKVRVKSEjg888/Z+TIkYwcOZJ58+aRmJhorthEGbRq1ariaWTWubN2XHhA/d57OO7aVbSvJ4QQxcDkpH7kyBECAgKYN28e8fHxxMfHM3fuXAICAjh27Jg5YxRlyPDhw4uvkdnbb0NQECqNBs+339bO6iaEEKWYyUl9/PjxPPvss1y7do2NGzeyceNGIiIieOaZZxg3bpwZQxRliY+Pj0GNzMzSF1ylgiVLUNq1Q33vHjbPPw8PrzRJX3MhRGlUqJr6e++9h63tv7flbW1teffddzly5IhZghMiL2brC+7gQNaGDWT6+KC6cAFeeAEyMvj66685ffo0X3/9tXkCFkKIYmByUndzcyMyMjLH+qioKN2Y8EIUFbP2BffyInbZMhQnJ9i2DUaNYviwYVSvXr1o+80bydz96YUQ1sfkpD5kyBCCgoJYv349UVFRREVFsW7dOkaOHMlLL71kzhiFyMHcfcHTGzVCs3YtqNWwciX+33xDUFBQieprLkldCFEQo7q0Peqzzz5DpVIxdOhQMjMzAbCzs2P06NF8+umnZgtQiOKi9O0LS5bA6NHYTZ+Oh0YDzZpZOiwhhDCYyTV1e3t7FixYwN27dwkPDyc8PJz4+HjmzZuHg4ODOWMUokhpNBqSkpKIj49H8/rr8N57ANQMCUEdFmZymVKrFkIUN6OTukajYfbs2XTo0IHWrVszffp0atWqRePGjXFyciqKGEUZoFarzTZMq7E0Gg337t37NwnPmkXW4MGos7KwGzIEDhwwqjy1Wo2bmxtJSUmS1IUQxcrob9CZM2fywQcf4OLiQpUqVViwYAHBwcFFEZsoQyyZ1HMJhozly0lo0wZVSgo2/fphd+6cEYebYQ54IYQwgdHfOt988w1ffPEFW7duZdOmTfz666+sWbNGaiTCujg4cPHTT9E88QQ3ExJYNmgQ0Xv3WjoqIYTIl9FJPTIykqefflr3vHv37qhUKhmkQ5QqhtzzznRwIG71apZ5eXH6/n1W9u8PuXTjFEKIksLopJ6ZmYmjo6PeOjs7OzIyMswWlBBF7dGkHh0dzcqVK3NM+aooCgnA0F9/pWGFCryemAhdu0JUlEVillHuhBAFMbpLm6IoDB8+XK+Fe2pqKqNGjcLZ2Vm3buPGjeaJUIhCym7dntd0rqGhoVy5coUNGzbQrl07AF2iHz58OK1bt+a1337D5+WX4coV6NJFOx971arF+j4eHUVv2rRpxfraQojSweikPmzYsBzrXnnlFbMEI0RRyK6V59UQLzAwkOjoaAYPHqxb92iib926NVk+PmSFhWHbo4c2sXfurE3s1asX2/sICgoiKSmpeCa7EUKUSkYn9dDQ0KKIQwiL8fX1ZcSIEVSuXFm3LrdEj78/7NypvQR/6dK/ib1mzWKL05yj6AkhrI/0uREiF9mJ3svLS3+Dn582sdepo20016kTnDljkRiFEOJxktRFmZdXQ7k8+fpqE3uDBhAdrU3s+/cXaYxCCGGIUpHUP/74Y1Qqld5Sr149S4clrERoaChnz55l4sSJhrcs9/GB3bvhiSfg7l3o1g22bNFtlpbqQghLKBVJHaBhw4bcvHlTt/z999+WDkmYkSVHYQsMDCQtLQ1HR0fj5mevVAm2b4feveHBA3j2WVizBjDjfO9CCGEEk2dpK262trZ4e3tbOgxRRLKTevaMf4bub44fAb6+vkydOpWwsDDjW5Y7O8Mvv0BgIKxdC6+8ApGRBI0YIS3VhRDFrtQk9UuXLuHr64ujoyPt2rUjJCSEqvn0E05LSyMtLU33PCkpqTjCFMUkO6mbS6VKlRg+fLhpPxzt7eHbb6FyZViwAD74AL/z5xn73/+ataW6jCkvRNnyeN5ycHAocBbUUvHt0LZtW1atWsUff/zB0qVLiYiIoFOnTty7dy/PY0JCQnB3d9ct/v7+xRixMJWlEpeiKCQnJ5s+h4FaDfPnw6JFoFaj/uYbvF99Fe7cMVuMktSFKFv8/f318lhISEiBx6gURVGKITazSkhIoFq1asydOzfPy5u51dT9/f1JTEzEzc2tuEIVJUBmZibXr1/Hz88PW1vtxanIyEjmzZvH+PHj8fT05PDhwyiKQps2bXB0dCQ9PZ1z587h5OSEv78/t27d0js+P5rff4chQ1AnJ6PUqoVq82aoW7eo36YQwkokJSXh7u5OVFSUXr6ympr648qXL0+dOnW4fPlynvs4ODjg5uamtwiRraCGbLa2ttjY2LBkyRKjW7Brevbkxg8/kFGlCqrLl6F1a9i0yQxRCyHKksdzWEEJHUppUk9OTubKlSv4+PhYOhRRSgUFBVGvXr08r/So1Wo2bNjAhQsXTBpFMb1OHW5s3IjSsSPcuwfPPQeTJ4OBDQGFEMIUpSKpT5w4kV27dnHt2jX27dvHc889h42NDS+99JKlQxOlQG59xg0ZcjU78QcGBhr8Wo/O/pZVqRJZ27bB+PHajZ9+qu3+dvu2ye9FCCHyUyqS+vXr13nppZeoW7cuL7zwApUqVeLAgQN6Y3ULkRdT+4ybMta6RqMhMTERXVMVOzuYOxfWrdN2fwsLg5YtQcZZEEIUgVLRpW3dunWWDkGUYsbObpY9VauTkxNgplbnQ4ZAo0bw/PNw8aJ2MpgPP4QpU8CAxndCCGGIUlFTF6IwjK1xP3oJHczYlaxhQzhyBIYOBY0Gpk3Tzs3+zz85XlMIIUwhSV2UeWq1GhcXF1xdXYu+D7irK6xerR1O1s0N9u6Fpk1Rvv+ehLt3JakLIQpFkroo82xtbXWDPBTbwC7/+Q+Eh2snhElMxOaVV6j85ptg6ExxQgiRC0nqosxTq9Xcv3+fRYsWmW1WNZVKVfCPhBo1tDO9TZ2KYmuL8x9/YNO0KXz/PZS+MaGEECWAJHUhMN+satHR0cyaNYvZs2dz//79gmv+dnbw8cdk7d9Pev36qO7c0dbin38ebt4sVCxCiLJHkroQFDwYjaFWrFjBrl272Llzp3E/EJo1I/qXX8iaOlWb6Ddtgnr1YOFCGbBGCGEwSepCYFqf9NwEBQXRuXNnunTpYvwPBDs7lClTtC3kW7eGpCQYO1b7+MCBQsUlhCgbJKmLMqmoZjzz9fXlgw8+YPLkyUb9QNAb9a5JE9i/H778EipU0Daoa9cOXnsN4uLMGq8QwrpIUhdlUn5JPbdhZYtajnv6Njbwxhtw4QJkD1P79dcQEABz5kBqarHFJoQoPSSpC/GY7ARrykQupsrznn7lyrByJezZA82aaS/Jv/ee9n77unXSSl4IoUeSuhCPMWUil8Iq8J5+x45w9CisWgVVqsA//8BLL2n7ue/cWWxxCiFKNknqwuoZe/88O8H6+fkVyX13k4eEVath2DDt2PEzZmgniDl0CJ56Crp1k0lihBCS1IX1M7VRXFE1piv0OO9OTtqJYC5fhjff1HaB++sv6NQJevWSlvJClGGS1IUwI7Vajbu7OyqVquhfzNsblizRJvfXX9fO9rZtm7alfO/e2svycs9diDJFkroQZlRUtfu8aDQaEtzc0Cxdqr0sP2KEtuX81q3ay/Jt28JPP0FWVrHEI4SwLEnqQmDeZFyciV3vUn6NGrBihbYb3OjR4OgIhw/DoEFQvz4sWwb37xd5TEIIy5GkLgSWT+pm/SEQEABffKFtIT9linYAm0uXtP3e/fzgnXe0l+yFEFZHkroQxSy3wW2KpHbv6altJR8ZCfPmQc2acPcuzJ0LtWuj9OkDv/0ml+aFsCKS1IUoZuaaEc5gLi4wbpy2tv7bb2h690ZRqVD98Qc884y2Zj91KkREFE88QogiI0ldiGJmrhnhjKZWw9NPo/n1V27s2IFm/Hjtpfl//oHp07U1+aeegm++gZSU4o1NCGEWktSFeExRN3Qz14xwYPo49ZnVqqGZMwdu3IC1a6FHD1CptN3ghg3TdpcLDIQ//oCMjELHKYQoHpLUhXhMcXdLK4xCX8ovV0473Oy2bXDtmvYefEAAJCdrh6Tt0wd8fLT94MPCZG53IUq4kv+tJYTIkymX8h+t3et1iataVdta/tIl2L1bO1qdpyfcuQPLl0P37tpx50eP1tbg09KK8J0JIUwhSV2IUsyUS/mP1u5zHbJWpdIOObtkifby/Pbt2rncK1aE2FjtPO99+oCHh7YP/OrVMs+7ECWEJHUhyphHa/cF3pO3tdVOFrNsGdy6BVu2aPu7+/hoL9H/9BMMHw5eXtofArNmaSeZkW5yQliESlHKxuDQSUlJuLu7k5iYiJubm6XDEWVYZmYm169fx8/PD1tb22Iv69FjZsyYwaFDh2jTpg3Tpk0z/IU1Gjh2DH79Ff73PwgP199eoQJ07aptgNejh7ZlvRDCIIXJV4X7RhFCGK0kNcQLCgoiKSnJ+O51ajW0aqVdpk3TDnDz22/aBnd//aUd5Oann7QLaJN6587a2nynTtrGeMUx6Y0QZYzU1IUoxQpbUwfMdtXgkRfQjjn/55/a5cCBnK3mvb2hY8d/k3yTJtqJaIQQhcpXktSFKMU0Gg1JSUm4ubkZXPN/9BiNRmP+pP64e/e0ren37NEuhw/n7Pvu7AwtWkDr1tCmjfZvjRpSmxdlkiR1A0hSFyInU34UFNqDB9rEvmcP/P037N2rTfyPq1RJe3m/dWttwm/SRJvoS8BtCyGKkiR1A0hSF6KEysqC8+e1iT57OXEC0tNz7uvsDI0baxN89tK4MZQvX+xhC1FUJKkbQJK6EKVIWhqcOvVvkj95Ek6fznvAGz8/qFsX6tXTLtmP/fzkEr4odSSpG0CSuhClXGamdh74kye1NfmTJ7VLZGTexzg7Q5062gRfu7a2FX6NGtq/vr75Xsq/fv06S5YsITg4WNeoUIjiIEndAJLUhbBSCQlw7hxcuKC9jH/+vPbx5cv5j1Vvbw/Vq/+b5LP/Vq0Kfn5M/eILDh05YnwffiEKSfqpCyHKrvLloV077fKojAy4evXfZH/livZ5RIR2utn0dLh4Ubvk4nUbG3By4vXbt7XH+/npL1WqaEfSc3Ao+vcohIGkpi6EKHsyM7Xj2mcn+Uf/Xr8O0dHaUfMeigaWA68BOUbZd3fXJvfHF09P/eeVK4OLi9zjFwWSmroQQhjD1haqVdMuTz2Vc3tmJsTEaBP89et8tWwZxy9eRHF25uMKFf5N/OnpkJioXfKo8euxs9NOjFOpknbJfvz43+zH5ctrfzS4ukpXPmEQqakLIUQBIiMjmTdvHuPHj6dq1aralYqivZ8fE2PYkppauCBcXcHNTZvkDfnr7Jz3Ym9v0EtGR0ezfPlyXnvtNaNmAhSFU2Yayi1ZsoT/+7//49atWzRt2pRFixbRpk0bg46VpC6EMFWhB+lRFLh/H+LjtfPT37nz7+O8/t65o70CkFt//cKytc0/6Ts7g5MT006c4OTduzTx8WFqr17g6Ki3RN+/z/IdO3itf398/fxybNctDg5ypcEIZSKpr1+/nqFDh/Lll1/Stm1b5s+fz4YNG7hw4QKenp4FHi9JXQhRKqWlaZN7UlLef3Nbl5KSc3l8eN4C5NuWAJgGnASaAFMLKszWVnv7wd6+cH/zWmdjo32N3P7mt60w+6rV+ktu67LXq1QGt6coE0m9bdu2tG7dmsWLFwPaX87+/v68/fbbvP/++wUeL0ldCFHmZWTknuxTUiA5Wf/5/fvaHxSpqXkuN5KSWBYVxetublTJytLf/uCB9gqF+JdKZdAPgSTAPS7OehvKpaenc/ToUSZPnqxbp1ar6d69O/v378/1mLS0NNIeGX0qMTER0CZ3IYQos9Rq7f15V9dCF+UKvPPwcY5vVkXRNjhMTdX+OEhP1/6oyF5ye56Zadx+2dsyM7XDDWdlaR9rNP+ue3Tbo/vk9tzYfY390aIo/5aTj+zPMjtvZXNwcMChgC6UpSKpx8XFkZWVhZeXl956Ly8vzp8/n+sxISEhuQ4Y4e/vXyQxCiGEEOaka5T50NSpU/n444/zPaZUJHVTTJ48mQkTJuieJyQkUK1aNSIjI3F3d7dgZPpat27N4cOHS1S5xh5r6P4F7Zff9ry25bY+KSkJf39/oqKiStStFjnXhm03Zpuc66I7Vs61YYriXCuKQosWLTh69Khew8yCaulQSpK6h4cHNjY2xMTE6K2PiYnB29s712Pyukzh7u5eov5B2NjYFEk8hSnX2GMN3b+g/fLbnte2/I5xc3OTc23mYy15rvPbJufa/MfKuTZMUZ1rBwcHypsw+2Cp6GNgb29Py5YtCQsL063TaDSEhYXR7vGhIUuZ4ODgEleusccaun9B++W3Pa9tRfX5FQU514ZtN3VbSSLn2rDtcq7NX26paf2+fv16hg0bxldffUWbNm2YP38+P/zwA+fPn89xrz030vq97JBzXXbIuS475FwbplRcfgcYMmQIt2/f5qOPPuLWrVs0a9aMP/74w6CEDtpLGVOnTjXonoQo3eRclx1yrssOOdeGKTU1dSGEEELkr1TcUxdCCCFEwSSpCyGEEFZCkroQQghhJSSpCyGEEFZCkjqwefNm6tatS+3atfn6668tHY4oYs899xwVKlRg0KBBlg5FFKGoqCi6dOlCgwYNaNKkCRs2bLB0SKKIJCQk0KpVK5o1a0ajRo1Yvny5pUOymDLf+j0zM5MGDRqwY8cO3N3dadmyJfv27aNSpUqWDk0UkZ07d3Lv3j1Wr17Njz/+aOlwRBG5efMmMTExNGvWjFu3btGyZUsuXryIs7OzpUMTZpaVlUVaWhpOTk6kpKTQqFEjjhw5Uia/x8t8Tf3QoUM0bNiQKlWq4OLiQp8+fdi2bZulwxJFqEuXLriaYYYqUbL5+PjQrFkzALy9vfHw8CA+Pt6yQYkiYWNjg5OTE6CdoVNRFMpqfbXUJ/Xdu3fTr18/fH19UalUbNq0Kcc+S5YsoXr16jg6OtK2bVsOHTqk2xYdHU2VKlV0z6tUqcKNGzeKI3RhgsKeb1F6mPNcHz16lKysLJmlsYQyx7lOSEigadOm+Pn5MWnSJDw8PIop+pKl1Cf1lJQUmjZtypIlS3Ldvn79eiZMmMDUqVM5duwYTZs2pVevXsTGxhZzpMIc5HyXHeY61/Hx8QwdOpRly5YVR9jCBOY41+XLl+fEiRNERESwdu3aHBOAlRmKFQGUn3/+WW9dmzZtlODgYN3zrKwsxdfXVwkJCVEURVH27t2rDBgwQLd97Nixypo1a4olXlE4ppzvbDt27FAGDhxYHGEKMzD1XKempiqdOnVSvvnmm+IKVRRSYf5fZxs9erSyYcOGogyzxCr1NfX8pKenc/ToUbp3765bp1ar6d69O/v37wegTZs2nD59mhs3bpCcnMyWLVvo1auXpUIWhWDI+RbWwZBzrSgKw4cPp2vXrrz66quWClUUkiHnOiYmhnv37gGQmJjI7t27qVu3rkXitbRSM6GLKeLi4sjKysox6YuXlxfnz58HwNbWls8//5ynnnoKjUbDu+++WyZbTFoDQ843QPfu3Tlx4gQpKSn4+fmxYcOGUj+Fb1ljyLneu3cv69evp0mTJrp7tN9++y2NGzcu7nBFIRhyrv/55x9ef/11XQO5t99+u8yeZ6tO6oZ69tlnefbZZy0dhigm27dvt3QIohh07NgRjUZj6TBEMWjTpg3h4eGWDqNEsOrL7x4eHtjY2ORoMBETE4O3t7eFohJFRc532SHnuuyQc20cq07q9vb2tGzZkrCwMN06jUZDWFiYXG61QnK+yw4512WHnGvjlPrL78nJyVy+fFn3PCIigvDwcCpWrEjVqlWZMGECw4YNo1WrVrRp04b58+eTkpJCYGCgBaMWppLzXXbIuS475FybkYVb3xfajh07FCDHMmzYMN0+ixYtUqpWrarY29srbdq0UQ4cOGC5gEWhyPkuO+Rclx1yrs2nzI/9LoQQQlgLq76nLoQQQpQlktSFEEIIKyFJXQghhLASktSFEEIIKyFJXQghhLASktSFEEIIKyFJXQghhLASktSFEEIIKyFJXQghhLASktSFEEIIKyFJXQghhLASktSFEELkKSoqii5dutCgQQOaNGnChg0bLB2SyIdM6CKEECJPN2/eJCYmhmbNmnHr1i1atmzJxYsXcXZ2tnRoIhdSUxclSpcuXRg3bpylwygW1vZeLfl+7ty5g6enJ9euXbPI61szHx8fmjVrBoC3tzceHh7Ex8frtr/44ot8/vnnFopOPE6SujDJ7du3GT16NFWrVsXBwQFvb2969erF3r17gdKRsFQqVb7Lxx9/bFA5Rflehw8fzoABA4w6xlKf/caNG5kxY4bZY+jcuTMjRozId5+ZM2fSv39/qlevXqjXMuXzLkuOHj1KVlYW/v7+unVTpkxh5syZJCYmWjAykc3W0gGI0mngwIGkp6ezevVqatasSUxMDGFhYdy5c8fSoRns5s2busfr16/no48+4sKFC7p1Li4ulgir1KpYsaLZy1QUhePHjzN48OA897l//z4rVqxg69atZn/94pCeno69vb1FY2jWrBmZmZk51m/btg1fX18A4uPjGTp0KMuXL9fbp1GjRgQEBPDdd98RHBxcLPGKfChCGOnu3bsKoOzcuTPX7cOGDVMAvSUiIkJRFEVJTU1V3n77baVy5cqKg4OD0qFDB+XQoUO6Yzt37qyMHTtW93zz5s2Km5ub8t133ymKoihZWVnKrFmzlOrVqyuOjo5KkyZNlA0bNui9/oYNG5RGjRopjo6OSsWKFZVu3bopycnJ+b6n0NBQxd3dPddt+cWc33vdsmWL0qFDB8Xd3V2pWLGi0rdvX+Xy5ct5vte8Psv+/fvrHfP2228rkyZNUipUqKB4eXkpU6dO1ds/t3gK+twKKteQzzX7/eQVw+rVq5WKFSsqqampeuX2799feeWVV3J9/xcuXFAAZd++fXl+Rhs2bFAqV66st65z587KW2+9pYwdO1YpX7684unpqSxbtkxJTk5Whg8frri4uCgBAQHK77//nufnbUq8imLYeQ8ODlbGjh2rVKpUSenSpYuiKNp/27Nnz1YCAgIUe3t7xd/fX/nkk0907zG/z76g85tf2YZITU1VOnXqpHzzzTe5bp82bZrSsWNHg8sTRUeSujBaRkaG4uLioowbNy7HF56iKEpCQoLSrl075bXXXlNu3ryp3Lx5U8nMzFQURVHGjBmj+Pr6Kr///rty5swZZdiwYUqFChWUO3fuKIqin+jWrFmjuLq6Kr/++quu7E8++USpV6+e8scffyhXrlxRQkNDFQcHB90PjOjoaMXW1laZO3euEhERoZw8eVJZsmSJcu/evXzfU35JPb+Y83uvP/74o/LTTz8ply5dUo4fP67069dPady4sZKVlZXjveYlt6Tu5uamfPzxx8rFixeV1atXKyqVStm2bVu+n31Bn1tB5RryuWa/n7xiuH//vuLu7q788MMPumNiYmIUW1tb5a+//sr1/a9du1axsbFRUlJS8vyMxowZo/Tu3VtvXefOnRVXV1dlxowZysWLF5UZM2YoNjY2Sp8+fZRly5YpFy9eVEaPHq1UqlRJr+xHP29T4lUUw867i4uLMmnSJOX8+fPK+fPnFUVRlHfffVepUKGCsmrVKuXy5cvKnj17lOXLlxv02Rd0fvMq2xAajUZ58cUXc/zIe9SWLVsUe3v7XL8PRPGSpC5M8uOPPyoVKlRQHB0dlfbt2yuTJ09WTpw4odueW8JKTk5W7OzslDVr1ujWpaenK76+vsqcOXP0jlu8eLHi7u6udzUgNTVVcXJyylFrCwoKUl566SVFURTl6NGjCqBcu3bNqPeTV1I3JuaC3L59WwGUU6dOGXxcbkn98RpR69atlffee09vn0fLNeRzK6hcQz7XR183r/c2evRopU+fPrrnn3/+uVKzZk1Fo9HkWubEiROVBg0a5PmaiqKtOY8YMSJHLI++n8zMTMXZ2Vl59dVXdetu3rypAMr+/ft16x7/vI2NNze5nffmzZvr7ZOUlKQ4ODjkmmgL+uwLOr/5lW2IPXv2KCqVSmnatKluOXnypN4+J06cMOn/nTA/uacuTDJw4ED69u3Lnj17OHDgAFu2bGHOnDl8/fXXDB8+PNdjrly5QkZGBh06dNCts7Ozo02bNpw7d0637scffyQ2Npa9e/fSunVr3frLly9z//59evTooVdueno6zZs3B6Bp06Z069aNxo0b06tXL3r27MmgQYOoUKGCSe/T0Jhzc+nSJT766CMOHjxIXFwcGo0GgMjISBo1amRSPABNmjTRe+7j40NsbGye+xvyuRVUrrk+19dee43WrVtz48YNqlSpwqpVqxg+fDgqlSrX/Y8dO0bLli3zLfPBgwc4OjrmWP/o+7GxsaFSpUo0btxYt87Lywsg38/O2HjBsPP++Hs6d+4caWlpdOvWLUd5BX32BZ3f/Mo2RMeOHXXvIS/lypUDtO0bhGVJUhcmc3R0pEePHvTo0YMPP/yQkSNHMnXq1DyTuqGaN2/OsWPHWLlyJa1atdJ9gSYnJwPw22+/UaVKFb1jHBwcAO2X959//sm+ffvYtm0bixYt4r///S8HDx6kRo0ahYrLWP369aNatWosX74cX19fNBoNjRo1Ij09vVDl2tnZ6T1XqVT5fuka8rkVVK65PtfmzZvTtGlTvvnmG3r27MmZM2f47bff8tz/2LFj9OvXL98yPTw8uHv3bo71ub2fR9dl/7vK77MzNl4w7Lw/3sc7OynmpqDPvqDzm5CQkG+85pDdxa1y5cpF/loif9KlTZhNgwYNSElJAcDe3p6srCy97QEBAdjb2+u6vQFkZGRw+PBhGjRooLffjh07+OWXX3j77bf1yndwcCAyMpJatWrpLY92sVGpVHTo0IFp06Zx/Phx7O3t+fnnn016T4bEnNt7vXPnDhcuXGDKlCl069aN+vXr55p4isLj8Rj6uRXEmM81t88k28iRI1m1ahWhoaF07949zxiuXr1KQkJCgTX15s2bc/bsWYPfh7EMjRdMP++1a9emXLlyhIWF5bo9v8++oPNbUNnmcPr0afz8/PDw8Ciy1xCGkZq6MNqdO3cYPHgwI0aMoEmTJri6unLkyBHmzJlD//79AahevToHDx7k2rVruLi4ULFiRZydnRk9ejSTJk2iYsWKVK1alTlz5nD//n2CgoL0XqNOnTrs2LGDLl26YGtry/z583F1dWXixImMHz8ejUZDx44dSUxMZO/evbi5uTFs2DAOHjxIWFgYPXv2xNPTk4MHD3L79m3q169v0ns1JObc3muFChWoVKkSy5Ytw8fHh8jISN5///3CffAGyi2egj63ghj7ueYWg1qtrUP85z//YeLEiSxfvpxvvvkmz9c8evQoKpVKN/BJXnr16sXkyZO5e/euybdZ8mNovIDJ593R0ZH33nuPd999F3t7ezp06MDt27c5c+YMjRo1yvezN+T/RV5lP/7/zlR79uyhZ8+eZilLFJKlb+qL0ic1NVV5//33lRYtWiju7u6Kk5OTUrduXWXKlCnK/fv3FUXRdkV64oknlHLlyul183rw4IHy9ttvKx4eHgZ1aTt79qzi6empTJgwQVEUbUvc+fPnK3Xr1lXs7OyUypUrK7169VJ27dql279Xr1667md16tRRFi1aVOB7yq/1e0Ex5/Ve//zzT6V+/fqKg4OD0qRJE2Xnzp0KoPz888+5vtfc5NZQ7vFj+vfvrwwbNizfeAr63Aoq15DP9dEy8vpMsr366qu5dhd71Pvvv6/UqVMn388nW5s2bZQvv/wy11iyVatWTZk3b57eukfPR3ZcAwcOzFG+IfFmM/W8Z2VlKZ988olSrVo1xc7OTqlataoya9Ysgz77gs5vXmWbw4MHDxR3d3e9BofCcmTsdyFEsevWrRsNGzZk4cKFZinvt99+Y9KkSZw+fVp3RcAUvXv3platWixevFhvvbnjtSZLly7l559/Ztu2bZYORSCX34UQxeju3bvs3LmTnTt38sUXX5it3L59+3Lp0iVu3LhhVDuBR+Pau3cvO3fuZNSoUUUerzWxs7Nj0aJFlg5DPCQ1dSFEsalevTp3797lww8/ZOLEiZYOR+e5557j8OHDDBs2jE8++UTXMr6kxitEXiSpCyGEEFZCurQJIYQQVkKSuhBCCGElJKkLIYQQVkKSuhBCCGElJKkLIYQQVkKSuhBCCGElJKkLIYQQVkKSuhBCCGElJKkLIYQQVkKSuhBCCGElJKkLIYQQVkKSuhBCCGEl/h885okcpsjGEgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 512x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "PvI_plot_Step2 = HtoH.PvI(CatP, CatdP, CatI, Iscale=[1.0,3000.0], Pscale=[0.0,30.0], showfit='true', weighted='false', errorbars='true', Source=FullName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "59006181",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Power law index: -1.3950085397625662 ± 0.12463978016135387\n",
      "Coefficient: 2.664636817966021e+31 ± 1.6741964936924164e+32\n"
     ]
    },
    {
     "data": {
      "image/png": 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MmWJxmTk5OQqg5OTkaBBh+QoLC5XU1FSlsLDQqscxceaMori5KQooyh9/3DCuS5cu3TS+69/D9ftWpAxL/Pnnn8rUqVOVP//884ZxVOlnK4QGmjdvrnTv3l25ePGicZ3BYFC6deumvPDCCzaMrHyAsnbt2gpte+HCBaV58+bKxo0by/yt7tq1qzJx4kTj8+LiYiUkJESJjY29adm9e/dW4uPjKxRHZY6jKOa951q1aikffvhhhbY1V1Wdr+yiBuB6JfMvBwQEmKz/9NNPCQwMpE2bNsTExHDx4sVyyygoKCA3N9dkcVqBgdC7t/rYgWsBZKhf4axWrVpFYmIi27dvN6779NNP+fPPP3nxxReN69544w1q1KhxwyUtLc0Wb+GGJk6cyD333EP/ktuR17hy5Qr79u0zeU2v19O/f3927NihWQxVdZzi4mJWrlxJfn4+PXr00Kzcslx/DisoKNC0fCtOV2cZg8HA1KlTuf3222nTpo1x/b/+9S8aNmxISEgIv/76K88//zwpKSmsKeeEFxsb61ozxo0YAT/9pCYAzzxj62iEENfo2LEjHTp0IDk5mf79+3Px4kViYmJ47bXX8PX1NW73xBNP8OCDD96wLHtLkFeuXEliYiJ79uwp8/WzZ89SXFxMUFCQyfqgoCCSk5NLbf/GG2/wxhtvGJ9funSJnTt38tRTTxnXHT58mLCwsEodx1wHDx6kR48eXL58mRo1arB27Vpat25d6XJvJDQ01OT5jBkzePXVVzUr3+4SgIkTJ3Lo0CF++eUXk/WPP/648XHbtm0JDg6mX79+/PHHHzRt2rRUOTExMURHRxuf5+bmlvowncrw4fDUU7BjB2RkgJ39SAjh6m655RZj4+a5c+cSGBhIZGSkyTYBAQGlaj7N9cILL/Dmm2/ecJsjR47QsmXLSh0HID09nSlTprBx40a8vb0rXR6UToIefvhhRo4cyYgRI4zrbJEEtWjRgqSkJHJycvjiiy+IiIhg69atVk0C0tPTTaYD9vLy0rR8u0oAnnrqKb799lu2bdtGgwYNbrhtt27dADh27FiZCYCXl5fmH5ZdCwmBHj3UBGDtWpg40dYRCSszGAzk5ubi5+eHXm+Xd/PENVq0aMG2bds4efIk//nPf1i/fn2pf7frr37LUtbV77Wefvppxo4de8MymjRpUuG4b2Tfvn2cPn2aTp06GdcVFxezbds23n33XQoKCggMDMTNzY2srCyTfbOysqhXr16pMq9PgqpVq0bdunVp1qzZDWMx9zjm8vT0NMYQHh7Onj17mD9/Pu+9916lyy5PSa8Da7GLBEBRFCZNmsTatWvZsmULjRs3vuk+SUlJAAQHB1s5OgcyYoSaAKxZIwmACygZl6FGjRqSADiAW265hQ8++IAXXniBgQMH0qdPn1LbaHELoE6dOtSpU6cyoVZYv379OHjwoMm6yMhIWrZsyfPPP4+bmxtubm6Eh4eTkJDAsGHDAPX/bkJCgkm1fmV5enpWyXFKGAwGze/JVzW7SAAmTpzIihUr+Oqrr/D19eXUqVMA+Pv7U61aNf744w9WrFjB3XffTe3atfn111+ZNm0ad9xxR5ldTlzWiBHw7LOwZQucOQNV9CMghLi5W265hfT0dL744gsOHTpU5jZa3AKojLy8PI4dO2Z8npqaSlJSEgEBAcZah3fffZe1a9eSkJCAr6+vSVstAB8fH2rXrm2yPjo6moiICDp37kzXrl155513yM/PL3ULpCSGvLw84/OVK1cCGM8LoCY5bm5upfatyHGujb+i7zkmJobBgwcTFhbGhQsXWLFiBVu2bGHDhg0V+FTtmFX7GFQQUOZS0vUjLS1NueOOO5SAgADFy8tLadasmfLss8+a1UXCqbsBXqtTJ7U74HvvlRmXPXcDvFm3P3M/2+LiYuXcuXNKcXGxpnHaC5v/XxNmyc/PV3Q6nfL000/bOpRybd68uczf4oiICOM2M2bMUBo2bFhuGeV12V64cKESFhameHp6Kl27dlV27txZ5v4zZswo95xQsqSmppZ7/Jsd5/r4K/Kex40bpzRs2FDx9PRU6tSpo/Tr10/58ccfy42hsqrqfKVTFCsPIG8ncnNz8ff3Jycnx6r3VIqKijh58iQNGjTA3d0GFSxvvgkvvAD9+sGmTaXiqlevHqdOnbphfNe/h+v3rUgZlijvuOU9N7c8Z+Ps78/ZZGdnU7t2bQ4cOCA1l+KGqup8JTcOrazKx89/4AH17+bNUIFRtoQQVePAgQN4enrSqlUrW4ciBFDJBKCwsJD09HRSUlLIzs7WKianUuUJQJMm0LkzGAwOPShQVZJJjkRVOHDgAK1bt8bDw8PWoQgBWJAAXLhwgSVLltC7d2/8/Pxo1KgRrVq1ok6dOjRs2JDHHnus3AEhRBUpqQX4/HPbxmFD5pzUJQEQVWHq1Kns37/f1mEIYWRWAvD222/TqFEj4uPj6d+/P+vWrSMpKYmjR4+yY8cOZsyYQVFREQMHDuSuu+7i999/t1bc4kZKEoCtW+G6PrGuwmAwkJOTg4s0cRFCCLOZ1XJoz549bNu2jVtvvbXM17t27cq4ceNYunQp8fHx/PzzzzRv3lyTQF2dWYO+NG4MXbrAnj3qbYAJE6omSCGEEA7DrBqAzz77rNyT/7W8vLx44oknGDdunMWBOSprzWlvdjV1yWAiLnwbQAghRPk06QVw9uxZ1q9fz9dff01mZqYWRTosu5nT/v771b9bt4KL/5sIIYQordIJwJdffkmzZs2YOXMmM2bMoGnTpsTHx2sRm0OKioqiZcuWREVF2TaQRo2gWzdQFKkFEEIIUYrZCcC1QzQCzJw5k927d7N7927279/P6tWreemllzQL0BFcWz1vV3Pa/+tf6t9PP61UMQaDgby8PGklL4QQTsTsBCA8PJyvvvrK+Nzd3Z3T1ww4k5WVhaenpzbROQi77UY2ahS4uamNASvRI0MSACGEcD5mJwAbNmzg/fffZ/jw4cYGb6NGjaJevXoEBgbywgsvsHjxYmvEKswVFAQDBgCg/+wzGwcjhBDCnpidADRq1Ij169fz4IMP0rt3b5KSkjh27BgbN25k06ZNpKWlcffdd1sjVmGJhx8GQPfZZ2p7ACGEEIJKNAIcPXo0e/bs4cCBA/Tp0weDwUCHDh3w9vbWMj5RWcOGQfXq6I4dw/PAAVtHI4QQwk5YlAB89913vPXWW+zdu5cPP/yQuXPn8vDDD/Pss89y6dIlrWMUlVGjBgwdqj68pu2GEEII12Z2AvD0008TGRnJnj17+Pe//83s2bPp3bs3iYmJeHt707FjR77//ntrxCos9c9tAJ9vvoGiIhsHI4QQwh6YnQAsX76c7777jpUrV7Jnzx7++9//AuDp6cns2bNZs2YNb7zxhuaBikoYOBAlMBC3v/9Gv3mzraMRQghhB8xOAHx8fEhNTQUgPT291D3/1q1b8/PPP2sTndCGhwfKPyMDuq1caeNghBBC2AOzE4DY2FjGjBlDSEgIvXv3Zvbs2daIS2jMMHo0APqvv0Yn7TSEEMLlmTUbIMDDDz/MXXfdxfHjx2nevDk1a9a0QlhCcz16UBgaikd6OtU3bQKZpVEIIVyaWTUAaWlpANSuXZsuXbrc9OT/119/WRyY0JhOR/6QIQD4rFtn21iEEELYnFkJQJcuXfj3v//Nnj17yt0mJyeHDz74gDZt2vDll19WOkChnfxhwwCotm0bnD1r22CEEELYlFm3AA4fPszrr7/OgAED8Pb2Jjw8nJCQELy9vTl37hyHDx/mt99+o1OnTsydO1dGBLQzhc2aYejQAX1SErovvoCnnrJ1SEIIIWzErBqA2rVr8/bbb5OZmcm7775L8+bNOXv2LL//M9HMww8/zL59+9ixY4ec/O1U8ahRgMwNIIQQrs7sRoAA1apV4/777+f+f7qWCcdR/MADuL/4Irr//Q9OnIBGjWwd0k2VzLZYvXp1W4cihBBOw+K5AISDql+fy7fdpj7++GPbxlJBdjvdshBCODBJAFxQ3gMPqA/i40FOqkII4ZIkAXBBFwcNQvH3V28ByNDAQgjhkiQBcEGKtzfKQw+pT5YtM3v/jIwM5s+fT0ZGhsaRCSGEqCoWJQB//vkn33zzDbt379Y6HlFFDGPHqg++/BLOnTNr3/j4eJKTk4mLi9M+MCGEEFXC7ATgs88+45ZbbmHo0KH06NGDzp07c+bMGWvEJqwpPBzatoWCAjBzgqDIyEhatmxJVFSUlYITQghhbWYnADNnzuRf//oXycnJ/PjjjwC88MILmgcmrEyng3Hj1Mdm3gYICQlhypQphISEWCEwIYQQVcHsBOD48ePMmDGDW265hX79+vHJJ5+wUqaYdUwPPwweHrB3L/z6q62jEUIIUYXMTgCKiopMBmRp2bIlBoOBU6dOaRqYqAJ16sA/EwRZ0hhQVI6MbyCEsCWLGgF+9NFH/O9//yMvLw8Ad3d3Ll68qGlgooqU3Ab45BO1PYCoMpIACCFsyewEoFevXrz22mv07NmTmjVr0rx5cy5fvkxcXBybN2/mwoUL1ohTWMugQVC/Pvz9N3zzja2jEUIIUUXMTgC2bt1KTk4OKSkpfPLJJwwfPpzevXuzZMkS+vXrR61atWjVqpU1YhXW4OYGERHqYzu7DSDjDQghhPVYNBkQQPPmzWnevDkPlQwoA6SmprJ3717279+vSXCiikRGwhtvwIYNcPIk1Ktn64gAiIuLIzk5mfj4eOlyKIQQGtN0JMDGjRvzwAMP8MYbb2hZrLC2Zs3gjjvUeQEsnCDIGvezo6KiaNmyJZGRkZqVKYQQQmUXQwHHxsbSpUsXfH19qVu3LsOGDSMlJcVkm8uXLzNx4kRq165NjRo1GDlyJFlZWTaK2AldMyZAxsmTZle9WyMBkPEGhBDCeuwiAdi6dSsTJ05k586dbNy4kcLCQgYOHEh+fr5xm2nTpvHNN9+wevVqtm7dSkZGBiNGjLBh1E7m/vvB1xf++IO4V14xGeo3IyODuLg4MjMzbRykuJa0kRBCVIbFbQC09MMPP5g8X758OXXr1mXfvn3ccccd5OTkEBcXx4oVK+jbty+gjkffqlUrdu7cSffu3UuVWVBQQME13dpyc3Ot+yYcnY8PjBkDixbx2Nmz5F4z1G98fDzHjh1j4cKFuLm5MWnSJPR6u8gdXVpJG4m4uDhmzpxp63CEEBq7/rzl5eWFl5eXZuXb5a94Tk4OAAEBAQDs27ePwsJC+vfvb9ymZcuWhIWFsWPHjjLLiI2Nxd/f37iEhoZaP3BHN2ECAPU3biR61Chj1XtkZCTNmjUDMDbKcwRZWVksWLDAaa+QS9pISANJIZxTaGioyXksNjZW0/IrVQOQkJBAQkICp0+fLnXvd5mFXcoMBgNTp07l9ttvp02bNgCcOnUKT09PatasabJtUFBQuSMQxsTEEB0dbXyem5trkySgpJp22rRphIWFVfnxzXLrrXDHHei2bcN35Uro3BlQ78VHRUVRu3ZtFi9e7DCN8latWkVKSorTXiFLGwkhnFt6ejp+fn7G51pe/UMlagBmzpzJwIEDSUhI4OzZs5w7d85ksdTEiRM5dOhQpecX8PLyws/Pz2SxhWuraR3CP7UANT77DAoLTV4KDg52qBPOqFGjaNGihVwhCyEc0vXnMK0TAItrAJYuXcry5ct59NFHNQvmqaee4ttvv2Xbtm00aNDAuL5evXpcuXKF8+fPm9QCZGVlUc9O+qyXJyoqitzcXMc5CY0YgVK3Lu6nT1P8zTfw4IO2jshiQUFBTJ48uUoTFoPBQG5uLn5+ftJOQghh1yz+hbpy5Qq33XabJkEoisJTTz3F2rVr+emnn2jcuLHJ6+Hh4Xh4eJCQkGBcl5KSQlpaGj169NAkBmsJCQlh0qRJVK9e3THGfPf0RPmnS6DuvfdsHIzjkfH9hRCOwuIEYPz48axYsUKTICZOnMgnn3zCihUr8PX15dSpU5w6dYpLly4B4O/vT1RUFNHR0WzevJl9+/YRGRlJjx49yuwBYG8URSEnJ8emJwW9Xk/NmjUrdFVqGD8eRadD/9NPcN14DEIIIZyDxbcALl++zPvvv8+mTZto164dHh4eJq+//fbbFS5ryZIlAPTp08dkfXx8PGPHjgVg3rx56PV6Ro4cSUFBAYMGDWLx4sWWhu9yShKAoqKim2/csCGX+valekICLF0KGrc8FUIIYXsWJwC//vorHTp0AODQoUMmr+l0OrPKUhTlptt4e3uzaNEiFi1aZFbZwjIXHnlETQCWL4dXXrF1OEIIITRmcQKwefNmLeMQdubSHXegNG6MLjUVt9WroX17W4ckhBBCQ9JMWZRNr8fw+OMAuL3/vo2DEUIIobVKDQR0/vx54uLiOHLkCACtW7cmKioKf39/TYITtqVERMCMGegTE/E5fBj+GZhJCCGE47O4BmDv3r00bdqUefPmkZ2dTXZ2NvPmzaNp06YkJiZqGaOwlTp1jOMA1Fu92sbBmCcjI4MFCxZUaMZImVRHCOGKLE4Apk2bxpAhQzhx4gRr1qxhzZo1pKamcu+99zJ16lQNQ3QNdtt/fPJkAGpv2oSunGGX7VFcXBwpKSmsWrWqQts61GiNQgihgUrVADz//PO4u1+9i+Du7s5zzz3H3r17NQnOldhtAtClC4YePdAXFeHhQG0BoqKiaNGiBaNGjarQtjKpjhDC1VicAPj5+ZGWllZqfXp6Or6+vpUKStiXoqeeAsAjLg7d5cs2jqZiQkJCmDx5MkFBQRXa1pHmOBBCCC1YnACMGjWKqKgoVq1aRXp6Ounp6axcuZLx48czevRoLWMUNmYYMoSCevXQZWfjs3atrcMRQgihAYt7Afzf//0fOp2OMWPGGEeX8/DwYMKECcyZM0ezAIUdcHcn88EHabRgAX7x8RikjYcQQjg8i2sAPD09mT9/PufOnSMpKYmkpCRjTwCtpyy0d67QivzMffeh1KiB5++/o9+0ydbhCCGEqKRKDwRUvXp12rZtS9u2balevboWMTkcV2hFXlyjBoVjxgDgtnChjaMRQghRWWbdAoiOjmb27Nn4+PgQHR19w23NmQzI0UVFRZGbm2vVVuQltQzTpk0jLCzM4nLMmRXweoVPPIHHkiW4bdyIx++/Q4MGFsdhicrELoQQwpRZCcD+/fspLCw0Pi6PuZMBObqqaEV+bS3DzJkzLS6n5CRqCaVxYy4OHIjPhg34LVsGd95pcRyWqEjsBoOB3Nxcl62NEkKIijIrAbh2AqCPPvqIBg0alLoaUxSF9PR0baITRlVRy1ARuZGR+GzYgM/atRjOnoV69Wwaz/VKxlPw9va2dShCCGHXLK5Lbdy4MWfPni21Pjs7m8aNG1cqKFGavfRVL+jaFUPHjugLCtA50MBAQgghTFmcACiKUub6vLw8ufpyMhkZGcTFxZGZmQk6HUWTJgGgX7QILl2ycXRCCCEsYfY4ACWN/3Q6HdOnTze511pcXMyuXbvo0KGDZgEK24uPj+fYsWMsX76cxx57DMP991P08su4Z2TA8uUwYYJVj5+RkcHChQsr3QDSWZXc9vDz85MGkkKICjP712L//v3s378fRVE4ePCg8fn+/ftJTk6mffv2LF++3AqhOgZnbKkeGRlJs2bNGDt2rLrCw4Ocxx5TH//nP/DPQFDWEh8f7/TdLCvDbueREELYNbNrAEoaAkZGRjJ//nz8/Pw0D8qRVaaVvb0KCQkhKiqK4OBgY7uPvFGjCFi0CF1qKnz+uXHaYGuIjIwkLy/P5g0ghRDCmVh8mRofHy8nfxemVKuG4Z+2AMyZA+W0CdGCvTSAFEIIZ2JxAhAbG8uyZctKrV+2bBlvvvlmpYISjkGZMAFq1ICDB9F9/72twxFCCGEGixOA9957j5YtW5Zaf+utt7J06dJKBSUcRK1a8MQTAOjnzrVxMEIIIcxhcQJw6tQpgoODS62vU6eO2l1MuIZp08DTE9327Xjt2WPraIQQQlSQxQlAaGgo27dvL7V++/btcq/WlYSEQEQEAP6VrPlxxh4UQghhryz+pX3ssceYOnUq8fHx/Pnnn/z5558sW7aMadOm8VhJFzHhGp57DkWvp/pPP8Gvv1pcjKslAK4wjbQQwn5Z/Ev77LPPEhUVxZNPPkmTJk1o3LgxkyZNYvLkybzwwgtaxijsXbNmKCNHAtIWwByuMI20EMJ+WZwA6HQ63nzzTc6cOcPOnTv59ddfyc7OZvr06S43G6AAw3PPAaD7/HM4csTG0diOOVf1UVFRtGzZUsY3EELYRKXrWtPS0vj77785fvw4GzZs4Ouvv+brr7/WIjbhSDp0IH/gQHSKArNn2zoamzHnql7GNxBC2JLZIwGWOH78OMOHD+fgwYPodDrj5EAlV//FxcXaRCgcRs6UKfj8+COsXAmvvAKtWtk6pCpnL9M2CyHEzVhcAzBlyhQaN27M6dOnqV69OocOHWLbtm107tyZLVu2aBiicBRXWrfGMGyYOiqgi9YCyFW9EMJRWJwA7Nixg1mzZhEYGIher8fNzY2ePXsSGxvL5MmTtYxROICSe98nH39cXbFypUu3BRBCCHtncQJQXFyMr68vAIGBgcZGTw0bNiQlJUWb6ITDMN773rkThg9XawFmzbJ1WEIIIcphcQLQpk0bDhw4AEC3bt2YO3cu27dvZ9asWTRp0kSzAJ1BVlYWCxYscOr+3iYt2qdPV1euWgWHD9s2MCGEEGWyOAF4+eWXjfOPz5o1i9TUVHr16sV3333HggULNAvQGaxatYqUlBSn7u9tcu+7Q4ertQAu2hZACCHsncUJwKBBgxgxYgQAzZo1Izk5mbNnz3L69Gn69u2rWYDOYNSoUbRo0cK1WobPmKH+lVoAIYSwSxYlAIWFhfTr14/ff//dZH1AQIAMAlSGoKAgJk+e7Fotw9u3hxEj1FqAklsCQggh7IZFCYCHhwe/VmLMd1ei1+vx9/d3zcRo1izQ6eDLL0FmCtScq82dIITQlsW/HI888ohm97S3bdvGfffdR0hICDqdjnXr1pm8PnbsWHQ6ncly1113aXJsa3PpH+lbb4UxY9THMTFVfnidToe/v7/TfvYu/X9LCFFpFo8EWFRUxLJly9i0aRPh4eH4+PiYvP72229XuKz8/Hzat2/PuHHjjO0KrnfXXXcRHx9vfO7l5WVZ4KJqvfoqfPYZJCTApk3Qv3+Fd63sCU5OkEIIUT6LE4BDhw7RqVMnAI4ePWrymrnV3YMHD2bw4ME33MbLy4t69eqZF6SwvUaNYMIEmD8fXnhBvRVQwf8fJSfwoqIi68YohBAuyOIEYPPmzVrGcVNbtmyhbt261KpVi759+/Laa69Ru3btcrcvKCigoKDA+Dw3N7cqwhRlefFFiIuDffvU9gD332/riIQQwu5df97y8vLStPbb7LrR48ePGyf+qSp33XUXH3/8MQkJCbz55pts3bqVwYMH33DCodjYWPz9/Y1LaGhoFUZsPnOmkXU4devC00+rj196CeSKXgghbio0NNTkPBYbG6tp+WYnAM2bN+fMmTPG56NGjSIrK0vToK730EMPMWTIENq2bcuwYcP49ttv2bNnzw0nHYqJiSEnJ8e4pKenWzXGyjJnGlmHFB0NgYFw9CgsX27raIQQwu6lp6ebnMdiNG5MbXYCcP3V/3fffUd+fr5mAVVEkyZNCAwM5NixY+Vu4+XlhZ+fn8liz0yG0nVGfn7q1T+oDQMvXrRpOEIIYe+uP4dp3fjdIZtHnzx5kr///pvg4GBbh6IZl5hGdsIEaNgQ/voLzOglIoQQQntmJwAl/fCvX1cZeXl5JCUlkZSUBEBqaipJSUmkpaWRl5fHs88+y86dOzlx4gQJCQkMHTqUZs2aMWjQoEodV1QxLy+YM0d9PGcOZGbaNh4hhHBhZvcCUBSFsWPHGqsiLl++zBNPPFFqHIA1a9ZUuMy9e/dy5513Gp9HR0cDEBERwZIlS/j111/56KOPOH/+PCEhIQwcOJDZs2fLWABVrKRbnru7u+X960eNUrsE7twJr7wCH36ofaBCCCFuyuwEICIiwuT5I488Uukg+vTpc8OeBRs2bKj0MUTllSQAgPGv2XQ6tfr/tttg2TKYNEmdN0AjJb0pJk2aJAMACSHEDZidAFw7Gp8QFunRQ60JWLVK7R2waVOFBwe6mZLeFPHx8c7boFIIITQgl0iilCoZQnfOHLVNwE8/wfr1mhVb0psiMjJSszKFEMIZSQIgSqmSBKBRI5g6VX38zDNQWFih3QwGA+fPn8dgMJT5ukv0phBCCA1IAiBsJyYG6tSBlBRYvLhCu9wsARBCCFExkgAI2/H3h9deUx9Pnw5WHlFSCCHEVZIACNuKioLwcMjNVWsEhBBCVAmLZwMESEhIICEhgdOnT5eqkl22bFmlAhMuws0N3n1X7RkQHw+PPw7du1e62CppxyCEEA7M4l/HmTNnMnDgQBISEjh79iznzp0zWYSosO7doaTV/lNPwQ1meawoV0oAnHomSSGE1VhcA7B06VKWL1/Oo48+qmU8wg7p9Xpq1Khh3ZNpbCysWQP79kFcnFoTUEUcPVm4dibJmTNn2jocIYSDsPgX78qVK9x2221axiLsVJUkAEFBMGuW+jgmBv7+23rHuo4WCYAteyc4/UySQgirsPgXb/z48axYsULLWISre/JJaNMGsrOvTh3sIEoSAKDKaxNk7AMhhCUsvgVw+fJl3n//fTZt2kS7du3w8PAwef1tme5VmMvdHRYtgt694b33YMwYdc4AB3LtfAlCCGHPLE4Afv31Vzp06ADAoUOHTF6r7PTAwoXdcQeMG6dOFPTvf0NiombzBAghhLjK4gRg8+bNWsYhxFVz58LXX8OhQ/B//4f++eeN1eoyAqAQQmjDMZs92xlHb0Vud2rXVqcMBpg1C31qqny+QgihsUoNBHT+/Hni4uI4cuQIAK1btyYqKgp/f39NgnMUct/XCh55BD76CBIS1MaBP/wgtwKEEEJDFl9S7d27l6ZNmzJv3jyys7PJzs5m3rx5NG3alMTERC1jFK5Ip4MlS9Qpg3/8ET77zNYRCSGEU7E4AZg2bRpDhgzhxIkTrFmzhjVr1pCamsq9997L1JJpXoWojObN4eWX1cdTpsCZM7aNRwghnEilagCef/553N2v3kVwd3fnueeeY+/evZoEJwTPPQft2sHZs+owwUIIITRhcQLg5+dHWlpaqfXp6en4+vpWKighjDw91S6Bbm7w+efo1q61dURCCOEULE4ARo0aRVRUFKtWrSI9PZ309HRWrlzJ+PHjGT16tJYxClcXHq7WBAD6SZPQO8lkU9bqPWLLYYmFEI7D4l4A//d//4dOp2PMmDEUFRUB4OHhwYQJE5gzZ45mAQqVy3c1nD4d1q1Dd+QIAbNmwerVto6o0qzVe6QkAbD6/A1CCIdm8a+Dp6cn8+fP59y5cyQlJZGUlGTsCeDl5aVljAJJAPD2hvh4FL2eGuvWofv2W1tHJIQQDq3SZ5Pq1avTtm1b2rZtS/Xq1bWIyem4/MlbK926ofzTw0T/xBPSK0AIISrBrFsA0dHRzJ49Gx8fH6Kjo2+4rUwGdJUMFKQdw8yZFH37LZ5Hj8Jjj8HatTJAkBBCWMCsBGD//v0UFhYaH5dHJgNyLnZVg+HtzZl58wgZNgzdV1+pPQSiomwdlRBCOByzEoBrJwD66KOPaNCgQamTgqIopKenaxOdsAv2VoNR2Lo1hlmzcIuJUQcI6tMHmjbVpGyDwUBubi5+fn72kfAIIYSVWPwL17hxY86ePVtqfXZ2No0bN65UUMLxVHUtgTJtGvTuDfn58Oij8E9PlMqSLnRCCFdh8a+1oihlrs/Ly8Pb29vigIRjqvLbBG5u6mRBfn6wYwfExlbNcYUQwkmYPQ5ASeM/nU7H9OnTTVr+FxcXs2vXLjp06KBZgEKUq2FDWLRIrQGYORPuugs6drR1VEII4RDMTgBKGv8pisLBgwfx9PQ0vubp6Un79u155plntItQiBt5+GH45hv4/HN1CuFdu2wdkRBCOASzE4CShoCRkZHMnz8fPz8/zYNyRXbV0t6RlEwbvH07HD2K/qmnYPZsW0clhBB2z+KhgOPj4wE4fPgwaWlpXLlyxeT1IUOGVC4yF2NvLe0dSkAArFgBd96J/tNPqdG+PUybZuuohBDCrlmcAKSmpjJs2DAOHjyITqczNgosGQOguLhYmwiFuEZGRgbz589n2rRphIWFXX3hjjvUK/+XXiJg+nQMAwaAtEURQohyWVzfPHnyZBo3bszp06epXr06v/32G9u2baNz585s2bJFwxCFuCouLo7k5GTi4uJKv/jCCxgGDEB/+TJuo0dDXl6VxVWSmGRkZFTZMYUQojIsTgB27NjBrFmzCAwMRK/Xo9fr6dmzJ7GxsUyePFnLGIUwioqKomXLlkSVNfqfXg8ff4whOBhdcjI8+SSU011VazdMTIQQwg5ZnAAUFxfj6+sLQGBgoPHKp2HDhqSkpGgTnRDXCQkJYcqUKYSEhJT5ur5ePfQrV6rJwH//C8uXV0lcN0xMhBDCDlmcALRp04YDBw4A0K1bN+bOncv27duZNWsWTZo00SxAIcx2xx3w2mvq44kT4eBBqx/yZomJEELYG4sTgJdfftk4XOqsWbNITU2lV69efPfddyxYsMCssrZt28Z9991HSEgIOp2OdevWmbyuKArTp08nODiYatWq0b9/f37//XdLQxeu4PnnYdAguHQJRoyAc+dsHZEQQtgVixOAQYMGMWLECACaNWtGcnIyZ8+e5fTp0/Tt29essvLz82nfvj2LFi0q8/W5c+eyYMECli5dyq5du/Dx8WHQoEFcvnzZ0vCFs9Pr4ZNP1NECjx2Df/0LqrBnii3nFJAGiUKIitB01JmAgACLpgIePHgwr732GsOHDy/1mqIovPPOO7z88ssMHTqUdu3a8fHHH5ORkVGqpkAIE4GBsG4dVKsGP/wAr7xSZYe2ZQIgDRKFEBVhcQLQt29fZs6cWWr9uXPnzK4BuJHU1FROnTpF//79jev8/f3p1q0bO3bsKHe/goICcnNzTRbhgjp0gJITYWwsfPGFTcOpCtIgUQjncP05rKCgQNPyLU4AtmzZwrvvvsuwYcPIz883rr9y5Qpbt27VJDiAU6dOARAUFGSyPigoyPhaWWJjY/H39zcuoaGhmsUkHMzo0VAyP8XYsVXSKNCWpEGiEM4hNDTU5DwWq/Gsp5W6BbBp0yZOnTpF9+7dOXHihEYhaSMmJoacnBzjkp6ebuuQhC3FxkL//pCfD8OGQXa2rSMSQogbSk9PNzmPxcTEaFp+pRKA4OBgtm7dStu2benSpYtVRgCsV68eAFlZWSbrs7KyjK+VxcvLCz8/P5NFuDB3d1i5Eho3huPH4cEHobDQ1lEJIUS5rj+HeXl5aVq+xQlASWM/Ly8vVqxYwZQpU7jrrrtYvHixZsEBNG7cmHr16pGQkGBcl5uby65du+jRo4emxxJOrnZttVFgjRqQkAATJlTZSIFCCGFvLJ4MSLnuh/Pll1+mVatWREREmF1WXl4ex44dMz5PTU0lKSmJgIAAwsLCmDp1Kq+99hrNmzencePGvPLKK4SEhDBs2DBLwxeuql07tSZgyBC1cWDz5uqYAUII4WIqNRtgYGCgybqRI0fSokUL9u3bZ1ZZe/fu5c477zQ+j46OBiAiIoLly5fz3HPPkZ+fz+OPP8758+fp2bMnP/zwA97e3paGL1zZPffAO+/A5MnwwgvQtCncf7+toxJCiCqlU66/lHdSubm5+Pv7k5OTI+0BHFhRUREnT56kQYMGuLtbnL+qJk+GhQvB2xu2boWuXS0u//r9NI3TjGPr9Xqys7PJzc0lLCzM6scWQmivqs5XZv06REdHM3v2bHx8fIxX6eV5++23KxWYEFY3b57aIHD9erjvPti1Cxo0sHVUZtPr9dSsWRO9Xo/BYCAnJ8fWIQkhHIBZCcD+/fsp/Kfl9P79+8vdzpLRAIWocm5u8Nln0KsXHDgAgwaRsWoV8z/6iGnTphEWFmbrCCukJAEAbDLyoBDCMZmVAGzevBmAwsJC9Ho9S5cupXnz5lYJTIgq4eur1gDcdhscPcqye+4huXVr4uLiyhzpsioYDAZyc3Px8/NDr9d0tG4hhDCy6NfFw8ODX3/9VetYhLCN+vVhwwaoXZvHMzII//13osaMsVk4BoOB7OxssrOz5YpeCGE1Fl9ePPLIIzLZiHAeLVvC+vUEV6/Oa3/+SYNXXgEbnnwVRSEnJ0cSACGE1VjcRLioqIhly5axadMmwsPD8fHxMXldGgEKh9OtG4bPP0c/bBj6zz6DevXgrbdA2rQIIZyQxQnAoUOH6NSpEwBHjx41eU0aAQotXXtP3NqUQYM4O3cudaKj1V4C/v4wY4bVjyuEEFXN4gSgpEGgENZmMBg4f/48NWrUqJLj5Q8fTgDgFh0Nr74K1arBc89VybGFEKKqSBNjIcqgTJqkziAI6lDBCxfaNiAhhNBYpYcJO3z4MGlpaVy5csVk/ZAhQypbtBC29cILcPEizJ6tjhpYrRqMH2/rqIQQQhMWJwDHjx9n+PDhHDx4EJ1OZ5wcqOT+f3FxsTYRCmFLM2eqScBbb8Hjj4OnJ9iwi2BF6HQ6GUNACHFTFv9CTJkyhcaNG3P69GmqV6/Ob7/9xrZt2+jcuTNbtmzRMEQhbEing//8ByZOVKcOHjsWli2zdVQ3dO3QwEIIUR6LawB27NjBTz/9RGBgIHq9Hr1eT8+ePYmNjWXy5Mk3HCpYCIei08GCBWoCsHgxREVBQQFMmGDryIQQwmIWXyIUFxfj6+sLQGBgIBkZGQA0bNiQlJQUbaITwl7o9fDuuzBtmvr8ySdh/vxrXparbiGEY7H416pNmzYcOHAAgG7dujF37ly2b9/OrFmzaNKkiWYBCmE3dDq1LcDzz6vPp06FuXOB0glARkYG8+fPNybGQghhbyxOAF5++WXjMKWzZs0iNTWVXr168d1337FgwQLNAhTCruh0avfA6dPV588/r/YSuE5cXBzJyckWD5edlZXFggULrJZAlIytIEMNC+G6LG4DMGjQIOPjZs2akZycTHZ2NrVq1ZKRAIVz0+nU3gGenvDyy2oykJOj1gb8UwMQFRVFbm4uUVFRFh1i1apVpKSkVHpWwvJmFrx2cCW5bSGEa9L0mx8QECAnf+E6XnoJ/u//1MdvvaX2ECgsBCAkJIQpU6YQEhJiUdGjRo2iRYsWFicQJeRKXwhRHrNqAKKjoyu8rUwGJKzB7hrbPf00BAaqPQP++184exZWrwYvr0oVGxQUxOTJky1OIIQQ4mbMSgAq2rVPagGEtZQkAHYlIkJNAh54AL7/Hvr1g6++snVUQghxQ2YlADIBkBDluOce+Okn9e+uXbj16YPbhx9CgwZVGkZJ74Np06YRFhZWpccWQjiWStWjnj9/nrfeeovx48czfvx45s2bR05OjlaxCeFYuneHX36B0FB0yckEDx8Oe/ZUaQiV7X0ghHAdFicAe/fupWnTpsybN4/s7Gyys7N5++23adq0KYmJiVrGKFycQ/Wpb9UKtm9HadMG9zNncOvXD7780qwiMjIyWLBgAVlZWWYfPioqipYtW1a68aAQwvlZnABMmzaNIUOGcOLECdasWcOaNWtITU3l3nvvZerUqRqGKFydPV/VltnKPjSU4q1budinD7pLl+D++9WxA/6ZMOtm4uLiSElJYdWqVWbHU9neB0II11GpGoDnn38ed/erzQjc3d157rnn2Lt3rybBCQH2fVVbbjc7Pz9Of/ABhokT1ecvvgjjxsF102aXJSoqihYtWjBq1CgrRCyEECqLEwA/Pz/S0tJKrU9PTzfOESCEFhz2qtbdHcM778DCheoAQcuXQ//+cJOq/ZCQECZPnkxQUFCVhKk1GXtACMdgcQIwatQooqKiWLVqFenp6aSnp7Ny5UrGjx/P6NGjtYxRCMf21FOwfj34+sLPP0N4OOzebeuorEYSACEcg8VDAf/f//0fOp2OMWPGUFRUBICHhwcTJkxgzpw5mgUohK2UN4yuRe66Sz3pDxsGKSnQq5dxamFNj6Mxe45NCFE5Fn+jPT09mT9/PufOnSMpKYmkpCSys7OZN28eXpUcBU0IW7l2pEHNr2RbtryaBFy5AuPHwxNPYLh0qdRxdDod/v7+Nj/pytW8EM7L7F8Xg8HAm2++ye23306XLl2YNWsWzZo1o23btlSvXt0aMQpRZaw+1LCfn9otcPZsdVKh997D7c47cT95smrjEEK4PLN/XV5//XVefPFFatSoQf369Zk/fz4TS1o6CyFuTq9XZxH89luoWRPdnj0E33MPurVrbR2ZEMKFmJ0AfPzxxyxevJgNGzawbt06vvnmGz799FOpIhQOwa6qtO++G5KSULp1wy03F7cHH4RJk+DyZasfWqvBlezq8xRCmMXsBCAtLY27777b+Lx///7odDrHGKVNuDy7O2E1bEjx5s3kPP64+vzdd3Hr1Qv31FRNii/vRK/V4EplfZ4ONXKjEC7M7ASgqKgIb29vk3UeHh4U/jMPuhDO5kZJgyYnOw8PzsXEUPz111C7NrqkJELuuw/dJ59UePTA8pR3orfm4Er2PHKjEOIqs7sBKorC2LFjTVr6X758mSeeeAIfHx/jujVr1mgToRA2VpIA1KhRo1SjvGtPdjNnzqzUcZTBg9VbAqNHo//lF4iMVNsJLF2qTjdsgaioKHJzc0ud6K05uFJ5xxRC2BezE4CIiIhS6x555BFNghHC0Wh+smvQgOKNG7nw4ovUXLgQ3ZdfwvbtEBenthkwky1GUXTYkRuFcDFmJwDx8fHWiEMIh2SVk527OzmTJ+M7ahTukZFw5Ajccw88/ji89RbUqKHdsYQQLks6GQthr8LDYd8+KJld8/33oX172LzZpmEJIZyDQyQAr776KjqdzmRp2bKlrcMSTq6qWrPf8DjVqsG8eZCQAKGhcPw49O0Ljz0G589bNa6bxiaEcGgOkQAA3HrrrWRmZhqXX375xdYhCSdX0sDPktte5ozkV6FW8337wsGD8MQT6vMPP4TWrcHKgwdJi34hnJfFkwFVNXd3d+rVq2frMIQN2GpY3JIGfpGRkWbvWxKzOce5aUNCf39YsgRGj1ZrAI4ehREjYORIWLAApEW/EMIMDlMD8PvvvxMSEkKTJk14+OGHSUtLu+H2BQUF5ObmmizCMdkqAaiq1uzlHafc8QfuuAMOHIAXXwQ3N3VugRYt1AaCGo/HYclnIPMYCKGN689hBQUFmpbvEN/Qbt26sXz5cn744QeWLFlCamoqvXr14sKFC+XuExsbi7+/v3EJDQ2twoiFqLwbjlro7Q2vvw5790L37pCXB888g1vnzgQeOmTTk68kAEJoIzQ01OQ8Fhsbq2n5DvENHTx4MA888ADt2rVj0KBBfPfdd5w/f57PP/+83H1iYmLIyckxLunp6VUYsbBXTteorUOHq+MEBAaiO3yYGvfdh/6RR8CO36PdDckshB1KT083OY/FxMRoWr5DJADXq1mzJrfccgvHjh0rdxsvLy/8/PxMFiG0btRmjatds8vU62HcOEhJgSefVKcZ/uwzaNEC3ZtvorPi5EKWJlSSAAhxc9efw64dgVcLDpkA5OXl8ccffxAcHGzrUISD0XoMfLtIAEoEBMCiRSa3Bdxefpn6/fqhW7ECrHCylV4CQjguh0gAnnnmGbZu3cqJEyf43//+x/Dhw3Fzc2P06NG2Dk04GEsatTncbYNOnWD7dgwffURx/fq4Z2TgFhEBXbvC1q2aHsqakwoJIazLIRKAkydPMnr0aFq0aMGDDz5I7dq12blzJ3Xq1LF1aMIFxMfHO95Vrl6P4V//4s8NG/j76adRfH3VUQX79IGhQ+HQIU0OI+P+C+G4HCIBWLlyJRkZGRQUFHDy5ElWrlxJ06ZNbR2WcBGRkZEOe5WreHtzfsIEipOTUZ54AsXNDb7+GrdOnQh55hn0N2hHI4Rwbg6RAAhhS05xlVu3LsULF5Lxww8Y7r8fnaLg+eWX6Nu0URsQnjhh6wjLJQ0GhbAOSQCEKEdV9Wevyn7zhc2aYfjsM0hMhHvvheJiiI+HW25RexDYYXdZSQCEsA5JAIQohzMkADqdDn9//9Jld+wI33wDO3ZA//7qCIJLlkCTJle7FAohnJokAELYKS16H9w0uejeHTZuhC1b4M47oahIrRFo1QoeeAB9UpKM6ieEk5JvtRB2qrJ97M1KIHr3hp9+UmsEhgwBRYEvvkDfpQs1R41Cv22buk4jDte1UggnJAmAEHaqsn3sLUoguneHr75Spx5++GF1sqEff1RrB8LD4eOPQYMJSWQAISFsTxIAIexUZXsfVCqBaNMGPvlEnXJ4wgR18qH9+yEiAho2hJkzISvLorgqHZsQQhOSAAjhpDTpvtikCSxerPYOeOMNCAlRT/yvvgphYeijovA8eNCqscntAiGsQxIA4VJcearaSp1IAwMhJkYdL+Czz6BbN7hyBf3HHxMyZAhuXbvC++/DDabotpTcLhDCOlzvV1C4NFdOADQ5kXp4wEMPwc6dsGMHhoceQvH0RLd/P/z732oNwb//rY4zoBG5XSCEdbjer6AQLkrzE2n37hj++1/Sd+ygeO5cdTChvDy1JiA8HLp0UW8f/P13pQ7jFCMxCmGHJAEQ4iacpdbAGidSvV6PX5Mm6J5+GpKTYfNmGD0aPD3VaYknTkQJDkYZPhzWrYMrVzQ7thCichz7F02IKuAsCYA1mHw2Op062+CKFXDyJLz9NkqHDugKC9GtWwfDh0NwMDz1FOzerem4AkII88kvmhBOyqaJS506MG0axXv28Nf332N4+mn15J+dDYsW4X777dTv0wf9iy+q7QUkGRCiykkCIITG7GXyGnupuShs2RLDnDlqV8ING+Dhh1GqVcMjLQ39f/6jthdo3lztZbB/vyQDQlQRSQCE0JhWCYC9nMA14+YGAwfCJ5+gZGWRHx+PMnIkVKsGf/wBc+ZAp05qMvD887B9uzpboRDCKpzkl0UI5+N0CcA19L6++Iwdi+6LL+D0aVi5EkaMUEcc/OMPmDsXevaEevVwGz+eOr/8gv7iRVuHLYRTcb5fFiGEzVxf+1GhwYdq1IBRo+DLL9Vk4LPP1J4E/v5w9iy6jz7C59FH0detC3ffDUuXqrcThBCVIgmAEEIz1ycAZg8+5OurDjS0YgWcOQMJCTB1KjRurE5C9P336twEYWHqlMVTp8J330F+vtXekxDOyt3WAQghnFdUVBS5ubmWDT7k4QF9+6rL22/D4cPw9dfwzTewa5c67kByMsyfr4470LOn2sZg0CBo1w6c8NaJEFrSKYprNLnNzc3F39+fnJwc/Pz8bB2OcGJpaWnMmzePadOmERYWZutwjAwGA7m5ufj5+VmtXUFRUREnT56kQYMGuLu7l3qumXPn4Kef1F4FGzZAWprp67Vrwx13QO/e6tgEbdtKQiAcRlWdr+QbIYTG7HXyGqdqVFirFowcqQ47fOIEpKTAwoVw773g46MOP7x2rXqLoEMHdTKjoUPVmoTEROldIARyC0AIzVWq2tvBlTT6q9LaD51OnYfgllvUUQavXIF9+2DrVnX55Re1xuDrr9UFwM8PpWtXCjp1wvOOO9DfdpuaVAjhQuQWgBAas1q1twOYMWMGu3fvpmvXrsycOdM+PouiIvWqvyQh+PlnyM0tvV3LltC9O/Toof699VZ17AIhqlhVna9c69dJCGFVdln74e4OXbuqy7PPqtX/Bw+Svn49Sz/9lCcvX6Z+aurVRoXLl6v7+fhAx47q4ETh4erfli3V8oRwAvI/WQihGYeYutfNDTp04MO1a0ls2JD3u3Zl5qRJas+CHTtg5071cV6eevvgl1+u7lutGrRvb5oUtG6t9kIQwsFIAiCEsBp7bnhoUlsRGAj33KMuoNYSpKSobQkSE68ueXlqgrBz59WC3N3V9gdt20KbNlf/Nm4sPQ+EXZM2AEJozC7ue9uII713s2M1GODYsdJJwfnzZW9fvbrajqAkKWjZElq0gIYNpW2BuCFpAyCEg7Lnq15rc+r3rtdf7W0werS6TlHgr7/g4EF1OXRI/XvkCFy8CHv2qMu1vLzUCY9atLi6lCQH/v5V/76Ey5IaACGES7LqwEhFRWptQUlCcOiQekvh99/VborlCQpSE4wmTUovQUFql0fh9KrqfCUJgBBCVJXiYvjzT7W3QUqK6ZKZeeN9q1UrnRQ0bqzeUggNhZo1JUFwEpIAaEwSACGEXcvNhaNH1VqC1FQ4fvzqkp6utkG4ER8fdZKk0FDT5dp11atXzXsRlSIJgMYkARDCcZw8eZJFixYxceJEGjRoYOtwbO/KFXW+g2uTgpIkIS0Nzp6tWDkBAVC/PgQHX13q1Sv9vEYN674fcUOSAGhMEgAhHMf1IwqKm7h4EU6eVGsKSpa0NNPnFy5UvLwaNUwTgnr1oE6d0ktgoJpUOGOjTxuSXgBCCJdllyMK2rPq1a/2UChPTo6aFGRkqO0NTp1S/16/XLyojnfw++/qcjN6vTr74rVJwbVJQkCAOs9CyVLy3MNDu/cvLCI1AEIIs1m7ir4qpi4WZVAU9eR/fVKQlQVnzqjL2bNXH+fkWH4sHx/TxKC8pWZN8PMDX1/1b8nixKMvSg2AEMJuffDBByQlJfHBBx9YpYq+ZDwBUcV0OvVE6+t749qEEleuqFMvlyQE1ycIZ85AdrY6G2PJUpI05Oery8mTlsXq5VV2YlCyXL/ex0etKfHxKXvx9na5XhSSAAghzCZV9AJQr8JL2gpQwZqh4mI1CTh3rnRyUNaSk6O2X8jNVZeLF9VyCgquJhla0OnKTxCuX1+9utot09v76t/rH9/sNTsYDdKhbgEsWrSI//znP5w6dYr27duzcOFCunbtWqF95RaAENqRKnpRlldffZXExEQ6derEq6++etPtMzIy+OCDD3jssccqPoFUUdHVhODaxKBkKWtdbq5a23Dx4tWah5KloKByb9pSHh5lJwleXuS6u+P/v//JLYASq1atIjo6mqVLl9KtWzfeeecdBg0aREpKCnXr1rV1eEK4FKmiF2V5/PHHjSf0inj//fdJTExEUZQKJQyAOvlSSfsALRQXl50YlJcwlKy/fFldLl26+vj659c/Liq6etzCQnUxp3eGxhymBqBbt2506dKFd999F1CvQEJDQ5k0aRIvvPBCqe0LCgoouCazy8nJISwsjPT0dKkBEEIIO/DXX38ZE4b69evbOhzrKypSaxyuTRgKCtTkoOTvlSvknj9P6BNPkJaWhv8180N4eXnh5eWlXTyKAygoKFDc3NyUtWvXmqwfM2aMMmTIkDL3mTFjhgLIIossssgii1MsM2bM0PTc6hC3AM6ePUtxcTFBQUEm64OCgkhOTi5zn5iYGKKjo43PDQYD4eHhJCYmonOQlp5dunRhz/UziTnR8bUuX4vyKlOGJftWdJ/c3FxCQ0OlBssMtv7+mMvW8cr33fr7VnSfkhrrP//80+RWm6ZX/zhQGwBzlVVV4uXlZVKdYu/c3Nxs+mNv7eNrXb4W5VWmDEv2NXcfPz8/SQAqyNbfH3PZOl75vlt/X3P3qVmzplX/TRyi+W5gYCBubm5kZWWZrM/KyqJevXoVLmfixIlah2ZVto7X2sfXunwtyqtMGZbsa+t/Y2fmaJ+treOV77v197X1v/H1HKoRYNeuXVm4cCGgVumHhYXx1FNPldkIUAhnIt1YhXAdMhLgdaKjo4mIiKBz58507dqVd955h/z8fCIjI20dmhBW5+XlxYwZMzS/ByiEsD9V9X13mBoAgHfffdc4EFCHDh1YsGAB3bp1s3VYQgghhMNxqARACCGEENpwiEaAQgghhNCWJABCCCGEC5IEQAghhHBBkgAIIYQQLkgSACEcTHp6On369KF169a0a9eO1atX33C9EMJxlfe9Pn/+PJ07d6ZDhw60adOGDz74wOyypReAEA4mMzOTrKwsOnTowKlTpwgPD+fo0aPk5uaWud7Hx8fWIQshLFTe993b25uCggKqV69Ofn4+bdq0Ye/evdSuXbvCZTvMQEBCCFVwcDDBwcEA1KtXj8DAQLKzswkNDS1zvSQAQjiuG33fq1evDkBBQQGKomDu9bzcAhCiim3bto377ruPkJAQdDod69atK7XNokWLaNSoEd7e3nTr1o3du3eXWda+ffsoLi4mNDS0QuuFEFXLmt/38+fP0759exo0aMCzzz5LYGCgWbFJAiBEFcvPz6d9+/YsWrSozNdXrVpFdHQ0M2bMIDExkfbt2zNo0CBOnz5tsl12djZjxozh/fffr9B6IUTVs+b3vWbNmhw4cIDU1FRWrFhRasK8m1KEEDYDKGvXrjVZ17VrV2XixInG58XFxUpISIgSGxtrXHf58mWlV69eyscff2yyb3nrhRC2p/X3/VoTJkxQVq9ebVY8UgMghB25cuUK+/bto3///sZ1er2e/v37s2PHDgAURWHs2LH07duXRx991LhdeeuFEPapMt/3rKwsLly4AEBOTg7btm2jRYsWZh1fGgEKYUfOnj1LcXExQUFBJuuDgoJITk4GYPv27axatYp27doZ7yf+97//JScnp8z1bdu2rcq3IISooMp83y9dusTjjz9ubPw3adIks7/rkgAI4WB69uyJwWAo87Xy1gshHNONvu9JSUmVKltuAQhhRwIDA3FzcyvVmCcrK4t69erZKCohhDXY+vsuCYAQdsTT05Pw8HASEhKM6wwGAwkJCfTo0cOGkQkhtGbr77vcAhCiiuXl5XHs2DHj89TUVJKSkggICCAsLIzo6GgiIiLo3LkzXbt25Z133iE/P5/IyEgbRi2EsIRdf9/N6jMghKi0zZs3K0CpJSIiwrjNwoULlbCwMMXT01Pp2rWrsnPnTtsFLISwmD1/32UuACGEEMIFSRsAIYQQwgVJAiCEEEK4IEkAhBBCCBckCYAQQgjhgiQBEEIIIVyQJABCCCGEC5IEQAghhHBBkgAIIYQQLkgSACGEEMIFSQIghBBCuCBJAIQQQggXJAmAEELYgfT0dPr06UPr1q1p164dq1evtnVIwsnJZEBCCGEHMjMzycrKokOHDpw6dYrw8HCOHj2Kj4+PrUMTTkpqAIQoQ58+fZg6daqtw7B7zvI5/f3339StW5cTJ07YLIbg4GA6dOgAQL169QgMDCQ7O9v4+kMPPcRbb71lo+iEM5IEQDidU6dOMWnSJJo0aYKXlxehoaHcd999JCQk2Do0TYwdOxadTodOp8PDw4OgoCAGDBjAsmXLMBgMVRrLmjVrmD17tvG5lglB79690el0fPbZZybrFy5cSEhIiCbHKPH6668zdOhQGjVqpGm5ltq3bx/FxcWEhoYa17388su8/vrr5OTk2DAy4UwkARBO5cSJE4SHh/PTTz/xn//8h4MHD/LDDz9w5513MnHiRFuHp5m77rqLzMxMTpw4wffff8+dd97JlClTuPfeeykqKqqyOAICAvD19dW8XEVR2L9/P8HBwXz55Zcmr+3bt49OnTppdqyLFy8SFxdHVFSUZmWWp0OHDrRp06bUkpGRYdwmOzubMWPG8P7775vs26ZNG5o2bconn3xi9TiFi1CEcCKDBw9W6tevr+Tl5ZV67dy5c4qiKMrly5eVSZMmKXXq1FG8vLyU22+/Xdm9e7fJtr1791amTJlifN6wYUNl3rx5Jtu0b99emTFjhnH7p556SpkyZYpSs2ZNpW7dusr777+v5OXlKWPHjlVq1KihNG3aVPnuu+9KHWfSpEnKs88+q9SqVUsJCgoyllmeiIgIZejQoaXWJyQkKIDywQcfGNcVFxcrb7zxhtKoUSPF29tbadeunbJ69Wqzjr969WqlTZs2ire3txIQEKD069fP+Ple+zlFREQogMmSmpqqfPTRR0pAQIBy+fJlk3KHDh2qPPLII2W+x5SUFAVQFi1apFSvXl3Jz883vta2bVtl+vTpN/yMzLF69WqlTp06pdYXFxcrb775ptK0aVPF09NTCQ0NVV577TVFUSz/976Zy5cvK7169VI+/vjjMl+fOXOm0rNnT/PfpBBlkBoA4TSys7P54YcfmDhxYpkNp2rWrAnAc889x5dffslHH31EYmIizZo1Y9CgQSb3Wy3x0UcfERgYyO7du5k0aRITJkzggQce4LbbbiMxMZGBAwfy6KOPcvHixVL7+fj4sGvXLubOncusWbPYuHGj2cfv27cv7du3Z82aNcZ1sbGxfPzxxyxdupTffvuNadOm8cgjj7B169YKHT8zM5PRo0czbtw4jhw5wpYtWxgxYgRKGW2H58+fT48ePXjsscfIzMwkMzOT0NBQHnjgAYqLi/n666+N254+fZr169czbty4Mt/Lvn378Pb2Zvz48fj5+fH9998DcPnyZY4cOaJpDcDPP/9MeHh4qfUxMTHMmTOHV155hcOHD7NixQqCgoKMr1v6710eRVEYO3Ysffv25dFHHy1zm65du7J7924KCgose7NCXMvWGYgQWtm1a5cCKGvWrCl3m7y8PMXDw0P59NNPjeuuXLmihISEKHPnzjWus6QG4Nors6KiIsXHx0d59NFHjesyMzMVQNmxY4fJca6/ouvSpYvy/PPPl/seyqsBUBRFGTVqlNKqVStFUdSryerVqyv/+9//TLaJiopSRo8eXaHj79u3TwGUEydOlHm86z+n65+XmDBhgjJ48GDj87feektp0qSJYjAYyiz3mWeeUbp27Wrc96GHHlIURVF27typAEpaWlqZ+1li6NChyrhx40zW5ebmKl5eXia1Kdey9N/7Rn7++WdFp9Mp7du3Ny6//vqryTYHDhy44b+HEOZwt2XyIYSWlAr0aP3jjz8oLCzk9ttvN67z8PCga9euHDlypFLHb9eunfGxm5sbtWvXpm3btsZ1JVePp0+fLnc/UFuDX79NRSmKgk6nA+DYsWNcvHiRAQMGmGxz5coVOnbsWKHjt2/fnn79+tG2bVsGDRrEwIEDuf/++6lVq5ZZcT322GN06dKFv/76i/r167N8+XJjY8ayJCYmGq/yR4wYwYgRIygoKCAxMZE6deqYNI57++23yc7O5rXXXgOgqKiI2rVr8/fff+PufvOfuEuXLuHt7W2y7siRIxQUFNCvX79y97P037s8PXv2vGkjzmrVqgFUuFZBiBuRBEA4jebNm6PT6UhOTta8bL1eXyrBKCwsNHnu4eFh8ryklf61z4FSP/Jl7Wdpa/4jR47QuHFjAPLy8gBYv3499evXN9nOy8urQsd3c3Nj48aN/O9//+PHH39k4cKFvPTSS+zatct4nIro2LEj7du35+OPP2bgwIH89ttvrF+/vtztExMTGT16NKD2LPDw8GDDhg1lNgA8dOgQd999t8ln0KhRowqd/AECAwM5d+6cybqSE+2NWPrvXRklt6nq1KmjWZnCdUkbAOE0AgICGDRoEIsWLSI/P7/U6+fPn6dp06Z4enqyfft24/rCwkL27NlD69atyy27Tp06ZGZmGp/n5uaSmpqq7RuopJ9++omDBw8ycuRIAFq3bo2XlxdpaWk0a9bMZLn2CvpmdDodt99+OzNnzmT//v14enqydu3aMrf19PSkuLi4zNfGjx/P8uXLiY+Pp3///uXGcPz4cc6fP2880bu7uzNkyBC+/PJLEhMTS92vP3ToEO3btzc+T0pKMrkSv5mOHTty+PBhk3XNmzenWrVqdtd19NChQzRo0IDAwEBbhyKcgNQACKeyaNEibr/9drp27cqsWbNo164dRUVFbNy4kSVLlnDkyBEmTJjAs88+S0BAAGFhYcydO5eLFy/esBtY3759Wb58Offddx81a9Zk+vTpuLm5VeE7M1VQUMCpU6coLi4mKyuLH374gdjYWO69917GjBkDgK+vL8888wzTpk3DYDDQs2dPcnJy2L59O35+fkRERNz0OLt27SIhIYGBAwdSt25ddu3axZkzZ2jVqlWZ2zdq1Ihdu3Zx4sQJatSoQUBAAHq9ep3xr3/9i2eeeYYPPviAjz/+uNxj7tu3D09PT9q0aWNcN3LkSGODupdeesm4XlEUkpOTTW5znDt3jpiYmJu+txKDBg0iJiaGc+fOGW9teHt78/zzz/Pcc8/h6enJ7bffzpkzZ/jtt9+qpLtgeX7++WcGDhxos+ML5yIJgHAqTZo0ITExkddff52nn36azMxM6tSpQ3h4OEuWLAFgzpw5GAwGHn30US5cuEDnzp3ZsGHDDe9rx8TEkJqayr333ou/vz+zZ8+2aQ3ADz/8QHBwMO7u7tSqVYv27duzYMECIiIijCdcgNmzZ1OnTh1iY2M5fvw4NWvWpFOnTrz44osVOo6fnx/btm3jnXfeITc3l4YNG/LWW28xePDgMrd/5plniIiIoHXr1ly6dInU1FTj4Dr+/v6MHDmS9evXM2zYsHKPmZiYSJs2bfD09DSuGzBgAMXFxVy5csXkFkBqaiq33HILe/fuNa4bPHgwbdu2ZfXq1WzcuJFz584xY8YMk4TiWm3btqVTp058/vnn/Pvf/zauf+WVV3B3d2f69OlkZGQQHBzME088UZGPzSouX77MunXr+OGHH2wWg3AuMheAEKLK9OvXj1tvvZUFCxZoUt7XX3/N6tWr+e9//2tc17BhQ7Zt20bDhg0B9ZbAjz/+yHPPPVduOevXr+fZZ5/l0KFDJgmUPVmyZAlr167lxx9/tHUowklIDYAQwurOnTvHli1b2LJlC4sXL9as3EOHDpm03cjPzycnJ8d48jcYDCxevJjp06ffsJx77rmH33//nb/++sus9hFVycPDg4ULF9o6DOFEJAEQQlhdx44dOXfuHG+++SYtWrTQrNxDhw7x4IMPGp8nJycbEwKDwcC0adOYMGECDRo0uGlZ9j6p0fjx420dgnAycgtACOGU5s6dy7p162jXrh0DBgww9o4QQqgkARBCCCFckH22dhFCCCGEVUkCIIQQQrggSQCEEEIIFyQJgBBCCOGCJAEQQgghXJAkAEIIIYQLkgRACCGEcEGSAAghhBAuSBIAIYQQwgVJAiCEEEK4IEkAhBBCCBckCYAQQgjhgv4fu/MfU+SnotUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 512x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Polarization fraction as a function of the column density\n",
    "PvN_plot_Step2 = HtoH.PvN(CatP, CatdP, CatN, Nscale=[2e+21,10e+22], Pscale=[0.0,30.0], showfit='true', weighted='false', errorbars='true', Source=FullName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c49996f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 512x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Polarization fraction as a function of the dust column density\n",
    "PvT_plot_Step2 = HtoH.PvT(CatP, CatT, Tscale=[15,28], Pscale=[0.0,30.0], CatdP=CatdP, errorbars='true', Source=FullName)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "491d0620",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving figures\n",
    "# PNG\n",
    "PvI_plot_Step2.savefig('Plots/'+SourceName+'_PvI_plot_Step2.png',dpi=300)\n",
    "PvN_plot_Step2.savefig('Plots/'+SourceName+'_PvN_plot_Step2.png',dpi=300)\n",
    "PvT_plot_Step2.savefig('Plots/'+SourceName+'_PvT_plot_Step2.png',dpi=300)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "PoLiteWIP",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
